telegram-mcp-cli
Allows AI agents and CLI users to interact with a personal Telegram account, providing tools for chats, message history, search, sending and editing messages, media, contacts, groups, admin, topics, reactions, polls, folders, and privacy settings.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@telegram-mcp-cliSend a message to @sarah saying 'See you tomorrow'."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Telegram MCP Server & CLI
Telegram MCP server and CLI for Claude Code and AI agents. 74 tools for chats, history, search, sending, media, contacts, groups, admin, topics, reactions, polls, folders and privacy, on your real account.
One install gives you both surfaces, the same tools under the same names, covering what the app does rather than what a bot is allowed to see.
Most Telegram integrations are bots, and a bot only ever receives messages sent to that bot. Your own conversations are invisible to it. This signs in as you over MTProto, so an agent can read the group you were actually talking in and answer in it.
Built and maintained by Navid Moazzez.
Two ways to use it
Command line
telegram-cli in your terminal, for scripting, cron, pipes, or just asking a
quick question without opening anything:
telegram-cli # every command, one line each
telegram-cli list-chats --unread-only --limit 10 # what needs an answer
telegram-cli history --peer @sarah --limit 20 # one conversation
telegram-cli search --query invoice # across every chat
telegram-cli send --peer me --text "note to self" # Saved Messages
telegram-cli list-chats --json | jq -r '.items[].name'
telegram-cli <command> --help # what any command takes--confirm is the shell spelling of the confirmation that deleting requires.
--json gives JSON, --compact puts it on one line, and errors are JSON on
stderr whichever you pick.
Reads return real objects rather than rendered text, so --json hands you
fields you can filter, and --fields id,text cuts the response before it is
ever printed.
MCP server, for AI agents
telegram-mcp is what Claude Code, Claude Desktop, Cursor and the rest launch.
You never run it by hand:
claude mcp add telegram \
-e TELEGRAM_API_ID=1234567 \
-e TELEGRAM_API_HASH=your_hash \
-e TELEGRAM_SESSION=your_session_string \
-- npx -y @thenavidm/telegram-mcp-cliThen just ask: "what did I miss in the group chats while I was asleep?"
Every other client is in section 4.
Which one
Where you are | What you can reach |
An agent that can run shell commands, like Claude Code or Cursor | Both. The CLI is the cheaper one: 175 tokens a turn against 2,218 |
claude.ai, the Claude Desktop chat tab, or a phone | The server only. There is no shell to run a command in |
A terminal, a script, cron or CI | The CLI only. There is no MCP client in a shell |
They are the same program reading the same tool definitions, so anything one can do, the other can.
Related MCP server: Telegram MCP Server
Features
Every tool is both a command and an MCP tool, with the same name. The command is the tool name with dashes.
Capability | CLI command | MCP tool |
Who am I |
|
|
Resolve a handle or id |
|
|
List chats |
|
|
One chat's details |
|
|
Read history |
|
|
Search messages |
|
|
Send a message |
|
|
Edit a message |
|
|
Delete messages |
|
|
Forward messages |
|
|
Mark a chat read |
|
|
Download media |
|
|
Send a file |
|
|
Check your setup |
| not a tool |
Sign in once |
| not a tool |
All 13 with their arguments are in section 7.
Contents
Section | ||
1 | Real prompts, not features | |
2 | Node 20 and one command | |
3 | api_id, api_hash, session string | |
4 | Every client, copy and paste | |
5 | What scripts branch on | |
6 | 2,218 tokens a turn, or 175 | |
7 | All 13, with arguments | |
8 | Why deleting asks twice | |
9 | The output format, and why | |
10 | Architecture | |
11 | What is stored and where | |
12 | Read this before you install | |
13 | When something breaks | |
14 | Including what an MCP server is |
1. What you can ask it
Real prompts, not a feature list. Each of these is one or two tool calls.
What did I miss in the group chats while I was asleep?
Find the last thing Sarah sent me about the invoice and reply that I will look at it tonight.
Search every chat for the wifi password someone sent me last year.
Which conversations have unread messages, and which actually need an answer rather than an emoji?
Save the PDF that Tom sent me this morning to my desktop.
Send myself a note in Saved Messages with these three links.
The reading tools are the ones worth having on. Searching a decade of chat for a thing you half remember is what this is genuinely better at than scrolling.
2. Quick install ⚡
Node 20 or newer. Nothing else.
npx -y @thenavidm/telegram-mcp-cli@latest --versionThat is the whole install. npx fetches it on demand, so there is nothing to
update later. Prefer it on your $PATH?
npm install -g @thenavidm/telegram-mcp-cliInstalling needs no account. Only signing in does, which is the next section.
Before you start
You need | Check with | If missing |
Node 20 or newer |
| |
A Telegram account | Open the app | Any account works, no Premium needed |
A phone you can receive a code on | The code arrives in the Telegram app, not by SMS |
You need an api_id frommy.telegram.org, not a bot token from BotFather. A bot cannot read your chats, which is the entire point of this. Section 3 walks through it.
3. Set up your account 🔑
Three values. The first two identify the application, the third is you.
The api_id and api_hash
Go to my.telegram.org, sign in with your phone
number, open API development tools, and fill in the short form. Any app name
and a short description are fine. You get an api_id and an api_hash.
These identify the software, not you, and they are not especially secret. They cannot read anything on their own.
The session string
export TELEGRAM_API_ID=1234567
export TELEGRAM_API_HASH=your_hash_here
npx -y @thenavidm/telegram-mcp-cli loginIt asks for your phone number, the code Telegram sends you, and your two-step
password if you have one. It prints the session string on stdout and everything
else on stderr, so telegram-mcp login > session.txt captures only the string.
export TELEGRAM_SESSION='the string it printed'What that string is
Full access to your account, and it does not expire. It is not a token scoped to some permissions, it is your login. Anyone holding it can read every message you have and send as you.
Keep it out of repos. Put it in your MCP client's config, which is a file only you can read, rather than in a shell profile that gets committed by accident.
Revoking
Telegram, Settings → Devices. The session shows up as a logged-in device
and terminating it invalidates the string immediately. Do that if it leaks, or
whenever you stop using this, then run login again if you come back.
4. Connect your client 🔌
npm install -g @thenavidm/telegram-mcp-cliOr run it without installing anything:
npx -y @thenavidm/telegram-mcp-cliNode 20 or newer.
Claude Code
claude mcp add telegram \
-e TELEGRAM_API_ID=1234567 \
-e TELEGRAM_API_HASH=your_hash \
-e TELEGRAM_SESSION=your_session_string \
-- npx -y @thenavidm/telegram-mcp-cliClaude Desktop
Settings → Developer → Edit Config, then add:
{
"mcpServers": {
"telegram": {
"command": "npx",
"args": ["-y", "@thenavidm/telegram-mcp-cli"],
"env": {
"TELEGRAM_API_ID": "1234567",
"TELEGRAM_API_HASH": "your_hash",
"TELEGRAM_SESSION": "your_session_string"
}
}
}
}Restart Claude Desktop afterwards.
Claude Desktop, as an extension
Build the .mcpb and double click it, which installs without touching JSON:
git clone https://github.com/thenavidm/telegram-mcp-cli
cd telegram-mcp-cli && npm install
bash desktop-extension/build.shIt asks for the three values in a settings panel and stores them as sensitive fields rather than plain text in a config file.
Cursor
Settings → MCP → Add new global MCP server, using the same JSON as Claude Desktop.
Windsurf
Settings → Cascade → Model Context Protocol, same JSON shape.
VS Code
code --add-mcp '{"name":"telegram","command":"npx","args":["-y","@thenavidm/telegram-mcp-cli"]}'Then set the three environment variables in your shell profile, or add an env
block to the entry.
Anything else
Any client that speaks MCP over stdio. The command is
npx -y @thenavidm/telegram-mcp-cli with the three variables in the
environment.
Docker
docker build -t telegram-mcp .
docker run --rm -i \
-e TELEGRAM_API_ID -e TELEGRAM_API_HASH -e TELEGRAM_SESSION \
telegram-mcpCheck it worked
telegram-cli doctorIt names any missing variable, says where to get it, and signs in to confirm the session actually works rather than only that it is present.
5. Output and exit codes
What gets printed
Reads return objects. A list comes back as {count, next_cursor, items}, so
paging is a field rather than something you infer.
telegram-cli list-chats --limit 3 --fields name,unread{
"count": 3,
"items": [
{ "name": "Sarah", "unread": 2 },
{ "name": "Design", "unread": 14 },
{ "name": "Mum", "unread": 1 }
]
}Errors are JSON on stderr, with the code and often a hint:
{
"error": "Telegram rate limited this account. Wait 42s.",
"code": "RATE_LIMIT",
"retryAfter": 42,
"hint": "Flood waits are per method and get longer if you keep calling. Wait it out."
}Exit codes
A script branches on the number.
Code | Means |
0 | Fine |
2 | Bad usage, or a write refused for want of |
3 | No such chat, user or message |
4 | The session is invalid or expired |
5 | Telegram rejected the call, or forbade it |
7 | Rate limited, |
10 | Nothing configured yet |
6. Which surface, and what each costs
Both surfaces carry the same tools. They differ in when you pay for them.
MCP server | CLI | |
Loaded every turn | 2,218 tokens | 175 tokens |
Loaded when Telegram comes up | nothing more | 1,271 more, once |
Listing the commands | included | 155, once |
Reading one command's arguments | included | 209, once |
Works on claude.ai and mobile | yes | no, there is no shell there |
Works in a script, cron or CI | no | yes |
You invoke it by | asking in plain language | typing a command |
An MCP server sends its whole tool list to the model on every turn, whether you mention Telegram or not. That is the price of being connected at all, before you ask anything.
The CLI is not free either, and it is worth being honest about that. Its shell skill carries a description that loads every turn so the agent knows the command exists. That is 175 tokens rather than 2,218, and the rest is only read when Telegram actually comes up.
Over 20 turns where Telegram comes up once, that is 44,360 tokens against 5,135. When the whole conversation is Telegram, the gap closes and the server is the better experience, because you ask in plain language instead of remembering flags.
Every number here came from a real tools/list handshake against this build,
counted with a tokeniser rather than estimated from character length.
Where the 2,218 goes
Worth knowing, because most of it is not something anyone can write away:
Part of the payload | Share |
JSON Schema structure: types, required lists, nesting | 70% |
Argument descriptions | 16% |
Tool descriptions | 14% |
Roughly 1,550 tokens are the protocol serialising every tool as JSON Schema. Any MCP server with this many tools pays the same. The 30% that is prose is what makes the tools usable without guessing.
For contrast, a Telegram MCP server shipping 80 tools pays that structural cost eight times over, on every turn, before anyone asks it anything.
How this compares
There are a dozen or so Telegram MCP servers. They cluster into three shapes, and the trade each one makes is worth understanding before picking any of them, including this one.
This server | Minimal servers | Comprehensive servers | Official channel plugin | |
Tools | 13 default, 74 available | 2 to 8 | up to 127 | n/a, a chat bridge |
Tokens every turn | 2,218, or 11,643 at full | ~400 to 1,500 | up to 21,096 | small |
Reads your real chats | yes | yes | yes | no, bot only |
CLI surface | yes, all 74 | no | no | no |
Choose what loads | yes, profiles | fixed | fixed | n/a |
Runs unconfigured | yes, self-diagnoses | varies | often crashes at import | n/a |
Transports | stdio, HTTP | stdio, some HTTP | stdio, HTTP, SSE | stdio |
Every number in the first and fourth columns was measured against a running server with a tokeniser, not read off a README.
Minimal servers collapse everything into a handful of very general tools, sometimes with a raw MTProto escape hatch. That is genuinely cheap and it is a reasonable design. The cost is discoverability: a model has to know the API to drive one general tool correctly, and the errors when it guesses wrong are worse than a missing tool.
Comprehensive servers go the other way, one tool per operation. Everything is discoverable, and you pay for all of it on every turn whether Telegram comes up or not. At the top of the range that is 21,096 tokens standing.
This one refuses the trade. Tools are named and discoverable like the comprehensive servers, but you choose how many load. The default is 13. The long tail lives in the CLI, which costs 175 tokens standing because a shell command is not sent to the model until it is typed.
The official channel plugin is a different thing entirely. It is a BotFather bot, so it can only ever see messages sent to that bot. Your own chats, groups and history are invisible to it. It is a good way to talk to Claude from your phone, and no way at all to let Claude read your Telegram.
Where the capability goes
Coverage does not require one tool per operation. Capabilities ride on arguments instead:
One tool here | Replaces |
| 4 separate tools |
| promote and demote |
| ban and unban |
| pin and unpin |
| react and remove reaction |
| 4 tools |
| add to folder, remove from folder |
| save and clear |
That is how the same ground is covered by 74 definitions rather than 127.
Spending less
Pick a smaller profile. TELEGRAM_TOOLS decides what is advertised:
Profile | Tools | Every turn |
| 13 | 2,218 tokens |
| 31 | 4,673 tokens |
| 74 | 11,643 tokens |
Turn the server off when you are not using Telegram. In Claude Code that is
@telegram to toggle, and every client has an equivalent.
Or install the CLI and skip the server. Every tool stays reachable and the standing cost falls from 2,218 to 175, which is the single biggest lever here.
Shape the responses. Once you are actually using it, --fields id,text and
a small --limit matter more than the tool list. See
section 9.
7. Tools
Every tool, with its arguments. Each is also a shell command under the same name
with dashes, so list_chats runs as telegram-cli list-chats.
Two things hold across all of them. Every list tool takes fields for
projection and a limit that is clamped rather than trusted. Every tool that
changes something is marked, and the irreversible one needs confirmation.
Account
Tool | Arguments | What it does |
| none | Which account this session is signed in as |
|
| A @username, phone or id to something you can act on |
Chats
Tool | Arguments | What it does |
|
| Recent conversations, newest first |
|
| One chat: name, kind, username, member count |
Reading
Tool | Arguments | What it does |
|
| Messages from one chat, newest first |
|
| Search text in one chat or everywhere |
|
| Save a photo, video, document or voice note |
Writing
Tool | Arguments | What it does |
|
| Send a message. Posts as you |
|
| Send a local file |
|
| Change a message you sent |
|
| Forward between chats |
|
| Clear a chat's unread count |
|
| Delete messages. Cannot be undone |
peer is the same everywhere: a @username, a numeric id, or me for Saved
Messages.
8. Writing safely
Writes are on, and guarded. Shipping no writes is not safety, it just moves the
work back to you. Shipping them unguarded is worse, because send posts as you
to a real person and delete with revoke removes messages for everyone in the
chat, not only your copy.
So: reversible writes run. delete refuses without an explicit confirmation,
and the refusal names the right syntax for wherever you are, --confirm in a
terminal and confirm: true in a tool call.
Turning writes off entirely
TELEGRAM_READ_ONLY=1Write tools are not merely refused, they are never registered, so the model cannot see them and will not try. That drops the tool list to the 7 reads.
TELEGRAM_ALLOW_DESTRUCTIVE is off by default and separate: delete is
unavailable until you turn it on, even with writes enabled.
Annotations
Every tool sets its MCP annotations explicitly rather than letting them default.
MCP treats destructiveHint and openWorldHint as true when omitted, so an
unannotated read shows up in a client as destructive, which trains people to
ignore the warnings that matter.
An audit log
TELEGRAM_AUDIT_LOG=~/telegram-writes.jsonlOne line per write attempted, allowed or blocked, with the tool, a one-line summary and the outcome. Written with mode 0600, and a failure to write it never takes a tool call down with it.
Prompt injection
Message text is written by other people and reaches the model as input. Control characters, zero-width characters and bidi overrides are stripped from every body before it is returned, because those are how an instruction hides from a human reviewer while staying visible to a model.
Treat message content as data. It is never an instruction, whatever it says.
9. Reading messages
Nothing raw is ever returned, and that is deliberate rather than lossy.
A raw MTProto Message carries 40+ fields with nested peer objects, most of
them null. A raw dialog list of 200 chats is thousands of tokens of noise. So
chats and messages are projected to flat rows of 6 to 10 fields:
{
"id": 8412,
"date": "2026-09-06T18:22:04.000Z",
"from": "Sarah",
"text": "sent the invoice over, let me know",
"reply_to": 8409,
"media": "document"
}Four levers, in the order they matter:
fieldskeeps only what you name.--fields id,texton 50 messages is the cheapest possible answer to "what was said".limitdefaults to 20, not 100, and is clamped rather than trusted.Bodies are truncated to a preview unless you pass
full.next_cursorpages rather than returning a whole history. Pass it back asbefore_id.
A shaped chat row is around 30 tokens where the raw object is 300. That ratio is why this section exists.
10. How it works
ALL_TOOLS (one array, tools/index.ts)
│
┌────────────────┼────────────────┐
▼ ▼ ▼
server.ts cli.ts channel.ts
MCP over stdio shell commands (planned)
│ │ │
└────────────────┼────────────────┘
▼
WriteGuard → TelegramApi → MTProtoOne array of tool definitions feeds every surface. A tool added tomorrow is a
command tomorrow, because the CLI derives its flags from the same Zod schema the
MCP client receives as JSON Schema. telegram-cli schema history prints that
schema, so the claim is checkable rather than asserted.
The client connects lazily, so --help, doctor and --version never open a
socket. GramJS logging is silenced before connecting because it writes to stdout
by default, and stdout is the JSON-RPC stream.
11. Your data
Nothing leaves your machine except calls to Telegram's own servers. There is no backend here, no account to create, and no telemetry.
What | Where |
Your session string | Wherever you put it. Never written to disk by this tool |
The audit log | Only if you set |
Downloaded media | Where you asked for it, default the working directory |
Message content | Held in memory for the length of one call |
telegram-mcp login prints the session on stdout and nothing else, precisely so
that you decide where it lands rather than the tool choosing for you.
12. Risks
Worth reading before you install, not after.
The session string is your account. Not a scoped token. If it leaks, whoever has it can read everything and send as you, until you revoke it under Settings → Devices.
An agent with this connected can message real people. That is the point,
and it is also the risk. TELEGRAM_READ_ONLY=1 exists for when you are pointing
something you do not fully trust at it.
Message text is untrusted input. Sanitising helps and is not a guarantee. Anything you would not want a model to act on unquestioned should not be in a chat it can read.
Telegram rate limits hard. FLOOD_WAIT on a new session is normal, the
waits get longer if you keep calling, and an automated retry loop can get an
account limited for hours. The error carries retryAfter so a caller can wait
the right amount instead of guessing.
Automating a user account is not what a bot account is. Telegram's terms allow user clients, but bulk or spammy behaviour through one is what gets accounts limited. This is built for reading your own chats and answering them.
13. Troubleshooting
Symptom | Cause and fix |
| One of the three variables is missing. |
| Session revoked or expired. Run |
| Flood wait. The error says how many seconds. Wait, do not retry |
| Use |
The server starts then exits | Usually a bad session string. |
Garbled JSON-RPC in a client | Something is writing to stdout. Open an issue with the client name |
| By design. |
Environment variables
Credentials
Variable | What it is |
| From my.telegram.org, API development tools |
| Issued with the api_id, same page |
| From |
Safety
Variable | What it does |
| Never registers a write tool, so the model cannot see one |
| Permits |
| Append-only record of every write attempted, allowed or blocked |
Tuning
Variable | What it does |
|
|
| Per-call deadline in seconds, default 30 |
Several accounts
Variable | What it does |
| A second account, for example |
Every account-scoped tool takes an optional account, matched loosely against
the label, so one server can hold a personal and a work account rather than
running two.
Pushing messages into a session
Variable | What it does |
| Allowlist path for |
telegram-mcp --channelRuns as a Claude Code channel, pushing real Telegram messages into a session that is already open. The official Telegram channel is a bot, so it only sees messages sent to that bot. This one is backed by your account, so an event can come from any chat you are actually in.
Nothing is forwarded until you allow a chat, which the allow_chat tool does.
That default matters: without it every message in every group you are in
becomes model input, which is both expensive and a prompt-injection surface.
Each allowed chat can carry a persona name, and it arrives on the event as
persona, so one session can answer as a different assistant depending on
which chat the message came from.
Running it always on
Variable | What it does |
| Port for |
| Interface for |
| Bearer token required on every HTTP request |
telegram-mcp --http --port=8787Binds to loopback, because a process holding a session string should not be
reachable from the network. Moving it off loopback without setting
TELEGRAM_HTTP_TOKEN hands your account to anyone who can route to the port.
Versions
See CHANGELOG.md.
14. FAQ ❓
An MCP server is a standard way to give an AI assistant real access to a tool, so it can act rather than guess. You install it once, your assistant gains the tools, and it works in Claude, Cursor and anything else that speaks the protocol. You never call the tools yourself, you just ask in plain language.
A bot is a separate account, and it only receives messages that people send to that bot. It cannot read your conversations, your groups, or anything that happened before it existed.
This signs in as you, over the same protocol the official apps use. Every chat you are in, all of the history, and search across it.
Telegram publishes the client API at my.telegram.org specifically so people can build clients, and third-party clients are common and long-standing.
What gets accounts limited is behaviour, not the API: bulk messaging, spam, mass adding people. Reading your own chats and answering them is what this is for. Rate limits are real and the tool surfaces them rather than retrying into them.
Telegram authenticates a user by sending a code to an existing session, so there is a one-time interactive login. What comes out is a session string, which is how the tool signs in afterwards without asking again.
It is full access to the account and does not expire. Treat it exactly as you would your password, and revoke it under Settings → Devices when you are done.
No. BotFather issues bot tokens, and a bot is the thing this deliberately is not. You need an api_id and api_hash from my.telegram.org, which is a different page and a different kind of credential.
Nothing leaves your machine except calls to Telegram. There is no backend here, no account to create and no telemetry. Your session sits in your client's config file and the audit log, if you enable one, sits where you pointed it.
It only acts when a model calls a tool, and a model only calls one in response to something you said. The risk is not spontaneity, it is misreading: a request to "reply to everyone" doing more than you meant.
That is what the guard is for. delete refuses without explicit confirmation,
TELEGRAM_ALLOW_DESTRUCTIVE keeps it off entirely by default, and
TELEGRAM_READ_ONLY=1 removes every write tool from the list.
Because every tool definition is sent to the model on every turn, whether you use it or not. 80 tools is 15,000 to 25,000 tokens of standing cost, and it makes tool selection worse: a model picks correctly from 13 far more reliably than from 80.
The 13 cover what actually gets used. The long tail belongs in the CLI, where it costs nothing until you type it.
Not yet. One session per server instance today. You can run a second instance with a different session string under a different name in your client config, which works but is clumsier than it should be.
Reading and sending work the same either way. Premium-only features like longer messages and larger uploads follow whatever your account already has, because this is your account rather than a bot with its own limits.
The MCP TypeScript SDK and GramJS both target modern Node. 20 is the oldest line still receiving security updates at the time of writing.
Questions
Run into a problem or have a question? Open an issue and I will help.
About the author
Navid Moazzez is a leading AI business strategist, and the host of the AI Creator Summit, watched by 100,000+ creators. He helps creators and founders master AI and build their own AI Operating System (AI OS) to automate their business and life. This Telegram MCP server is one piece of that system.
Links
Personal website: navid.me
Link in bio: navid.bio
Navid Media: navid.media
YouTube: @thenavidm and @thenavidai
X: @thenavidm
Instagram: @thenavidm
LinkedIn: thenavidm
If this is useful, star the repo and come say hi on X.
Dependencies
Library | License | What it does |
MIT | The MCP server and transports | |
MIT | The MTProto client, published as | |
MIT | Tool argument schemas and validation | |
ISC | Turns those schemas into what an MCP client receives |
License
MIT. Free to use, modify, and share.
Not affiliated with, endorsed by, or connected to Telegram Messenger Inc.
© 2026 NM Media. Made with ❤️ by Navid Moazzez.
Available Tools
13 toolsdeleteDelete messagesADestructive
Delete one or more messages. This cannot be undone, and with revoke it removes them for everyone in the chat, not only for you.
| Name | Required | Description | Default |
|---|---|---|---|
| peer | Yes | The chat the messages are in. | |
| revoke | No | Delete for everyone, not just this account. Default true. | |
| confirm | No | Must be true for this to run. This cannot be undone, so it is refused without it. | |
| message_ids | Yes | Ids to delete. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond the annotations by explicitly stating that deletion cannot be undone, that revoke affects all chat members, and that a confirm flag is required. This adds crucial behavioral details not present in the annotation flags (destructiveHint, idempotentHint).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, two sentences, with no redundant words. It front-loads the primary action and then explains key side effects and requirements.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple destructive operation, the description provides sufficient context: what it does, irreversible nature, the revoke effect, and the confirm requirement. No output schema is needed given the simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers all parameters with clear descriptions (peer, message_ids, revoke, confirm). The description does not add additional parameter semantics beyond what is already provided, keeping the baseline at 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete one or more messages') and the resource (messages). It distinguishes from siblings like 'edit' and 'send' by focusing on removal, which is unique among the listed tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context about the revoke option and the confirm requirement, implying when deletion is appropriate (e.g., permanent removal vs. local removal). However, it does not explicitly mention alternative tools or conditions for choosing delete over others, though none of the siblings directly compete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
download_mediaDownload media from a messageARead-onlyIdempotent
Save the photo, video, document or voice note attached to a message, and return the local path. The file is written to disk rather than returned inline, because a base64 image in a tool result is enormous and unreadable.
| Name | Required | Description | Default |
|---|---|---|---|
| dir | No | Directory to save into. Defaults to the working directory. | |
| peer | Yes | The chat the message is in. | |
| message_id | Yes | Id of the message carrying the media. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral details beyond the annotations: it explicitly states the file is written to disk, returns a local path, and explains the rationale for not returning inline. This complements the readOnlyHint (which concerns system state) and idempotentHint by clarifying the side effect of creating a local file.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the primary action and resource, and providing a concise rationale for the design choice. There is no redundant information, making it easy to scan and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no output schema, the description fully specifies what the tool does (saves media), what it returns (local path), and why it behaves that way. It is complete for an agent to decide when to invoke it and what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The tool description does not significantly enhance parameter understanding; it only lists media types and implies that peer and message_id identify the message. The parameter descriptions in the schema already cover the meaning adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (save media) and the resource (photo, video, document, or voice note attached to a message), and specifies the output (local path). It distinguishes the tool from siblings like send_file or forward by focusing on downloading media from a message.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (when media needs to be saved locally) and explains why it is used instead of returning inline (base64 is enormous and unreadable). However, it does not explicitly name alternative sibling tools, so it falls short of the highest 'explicit alternatives' level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
editEdit a messageAIdempotent
Change the text of a message you sent. Telegram marks it edited.
| Name | Required | Description | Default |
|---|---|---|---|
| peer | Yes | The chat the message is in. | |
| text | Yes | The replacement body. | |
| message_id | Yes | Id of the message to edit. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-readonly, non-destructive, and idempotent behavior. The description adds that Telegram marks the message as edited, which is a useful side effect, and clarifies that only messages you sent can be edited.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct and direct, conveying the essential action in one sentence without unnecessary elaboration. It is well-structured and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with three required parameters and no output schema. The description provides enough context for an agent to understand the operation and its side effect, making it complete for typical usage scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with brief descriptions. The tool description adds no further semantic detail beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to change the text of a message you sent. It uses a specific verb (change) and resource (message), and distinguishes from siblings like send (new message) and delete (removal).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context—use it when you want to modify a message you sent—but does not explicitly contrast with alternatives or state when not to use it. The context is clear enough for an agent to infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forwardForward messagesAIdempotent
Forward messages from one chat into another.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Chat to forward into. | |
| from | Yes | Chat to forward from. | |
| message_ids | Yes | Ids to forward. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, idempotentHint=true, and destructiveHint=false, which provide some behavioral context. The description adds little beyond stating the action; it does not clarify side effects like whether messages are copied or moved, but this is typical for forward operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant information. It is well-structured and directly conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple side-effect operation, the description is sufficient given the clear schema and annotations. It does not explain return values, but no output schema exists and the operation is straightforward, so this omission is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all parameters (from, to, message_ids) with clear descriptions (e.g., 'Chat to forward from.'). Since schema coverage is 100% and the description adds nothing beyond the schema, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action (forward) and resource (messages from one chat to another). It distinguishes itself from sibling tools like send, edit, and delete by describing a unique operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when you need to copy existing messages to another chat), but it does not explicitly mention alternatives or conditions for choosing this tool over others. The guidance is minimal and relies on inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_chatGet one chatARead-onlyIdempotent
Details of a single chat: name, kind, username, member count and description where the chat has them.
| Name | Required | Description | Default |
|---|---|---|---|
| peer | Yes | A @username, numeric id, or 'me'. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the nuance 'where the chat has them', indicating that optional fields may be absent, which is useful behavioral context. The readOnly and idempotent annotations already cover side effects, and the description does not contradict them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is direct and to the point, with no unnecessary content. It conveys the essential purpose and returned data efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides enough detail about the return fields for a simple tool, and the annotations cover safety attributes. It does not mention error handling or the format of the response, but given the tool's simplicity and lack of an output schema, this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully defines the 'peer' parameter with a clear description ('@username, numeric id, or 'me''), so the description does not need to add more. The schema coverage is 100%, giving a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns details of a single chat and enumerates the fields (name, kind, username, member count, description). It is distinct from sibling tools like list_chats, which handle multiple chats, and history, which deals with messages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a single chat's details are needed, but it does not explicitly contrast with sibling tools or state when not to use it. The context is clear enough, but a more direct comparison would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
historyRead chat historyARead-onlyIdempotent
Messages from one chat, newest first. Bodies are truncated to a preview unless full is set, because a long chat returned whole is mostly wasted context.
| Name | Required | Description | Default |
|---|---|---|---|
| full | No | Keep whole message bodies instead of previews. | |
| peer | Yes | A @username, numeric id, or 'me'. | |
| limit | No | How many messages. Default 20, max 100. | |
| fields | No | Comma separated fields to keep, e.g. 'id,text'. Dotted paths descend. Cuts response size. | |
| before_id | No | Only messages older than this id. Use next_cursor to page. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses non-obvious behavior: message bodies are truncated to previews unless `full` is set, and explains the rationale. This goes beyond the annotations, which only state read-only and idempotent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy. It front-loads the core purpose and then explains the truncated-body behavior efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the schema fully describes parameters and there is no output schema to explain, the description sufficiently covers all necessary context for invoking the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover all parameters, so the baseline is 3. The description adds no extra meaning for individual parameters beyond what the schema already provides, though it indirectly ties `full` to truncation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action (reading messages), a specific scope (one chat), and a key ordering detail (newest first). It clearly distinguishes from siblings like search or get_chat.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for retrieving a chat's message history, and the truncation note hints at when to set `full`. However, it doesn't explicitly compare with sibling tools like get_chat or search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_chatsList chatsARead-onlyIdempotent
Recent conversations, newest first. Returns a compact row per chat: id, name, kind, unread count and a short preview of the last message. Use fields to cut it down further.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | Only this kind of chat. | |
| limit | No | How many chats. Default 20, max 200. | |
| fields | No | Comma separated fields to keep, e.g. 'id,text'. Dotted paths descend. Cuts response size. | |
| unread_only | No | Only chats with unread messages. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful details about the output structure (compact rows, fields parameter), aligning with annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, uses two short sentences, and front-loads the core purpose (recent conversations) followed by output details and a tip about the 'fields' parameter. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple list operation and lack of an output schema, the description provides sufficient context (sort order, returned fields, field filtering) for an agent to understand the tool's functionality and expected results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides complete descriptions for all four parameters (kind, limit, fields, unread_only), so the description adds no additional parameter semantics. Per the rule, a baseline score of 3 applies when schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists recent conversations with a compact row per chat, including fields like id, name, kind, unread count, and preview. This distinguishes it from siblings like get_chat (single chat) and search (query-based).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving recent chats but does not explicitly compare with alternatives like search or get_chat, nor state when not to use this tool. The 'newest first' ordering provides some context, but explicit guidance is absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mark_readMark a chat readAIdempotent
Clear the unread count on a chat.
| Name | Required | Description | Default |
|---|---|---|---|
| peer | Yes | The chat to mark read. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover idempotency, read-only, and destructive nature. The description adds the basic action but does not mention side effects like read receipts or notification updates, which would be extra context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no unnecessary fluff. It is concise and clearly states the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, single-action tool with no output schema, the description is sufficient. It fully captures the purpose and leaves little ambiguity about the intended effect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'peer' has a clear description in the schema. The tool description does not add additional meaning beyond the schema, and schema coverage is high (100%), so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Clear' with the resource 'unread count on a chat', clearly distinguishing it from sibling operations like send, forward, edit, and delete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool instead of alternatives (e.g., get_chat, history, send). The description only states what the tool does, not when it should be chosen.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
resolveResolve a username or idARead-onlyIdempotent
Turn a @username, phone number or numeric id into a chat you can act on. Use it before sending to someone you only know by handle.
| Name | Required | Description | Default |
|---|---|---|---|
| peer | Yes | A @username, phone number, numeric id, or 'me'. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds that the result is a 'chat you can act on', which hints at the return type. However, it doesn't disclose edge cases (e.g., unresolved identifiers) or any limitations beyond annotations. Since the description carries minimal extra behavioral info, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, and the core purpose is front-loaded. Every word earns its place, and it's easily scannable for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, read-only, idempotent resolver with no output schema, the description covers the use case and hints at the return value ('chat you can act on'). It doesn't mention error handling or fallback behavior, but given the simplicity and annotation coverage, it's sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage for the single parameter 'peer' with its own description listing accepted formats including 'me'. The tool description merely repeats the same formats without adding new meaning. With full schema coverage, the baseline is 3, and the description adds no extra value here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'resolve' and the resource (username/phone/id into a chat), and explicitly positions it as a step before sending. It distinguishes itself from siblings like get_chat or search by focusing on converting a handle into an actionable chat.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear when-to-use: 'Use it before sending to someone you only know by handle.' It doesn't name alternatives explicitly, but the context implies that if you already have a chat reference, you wouldn't need this. This is adequate guidance for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchSearch messagesARead-onlyIdempotent
Search message text, either inside one chat or across the whole account when no peer is given.
| Name | Required | Description | Default |
|---|---|---|---|
| peer | No | Limit to one chat. Omit to search everywhere. | |
| limit | No | How many results. Default 20, max 100. | |
| query | Yes | Text to search for. | |
| fields | No | Comma separated fields to keep, e.g. 'id,text'. Dotted paths descend. Cuts response size. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds the scoping behavior (peer vs no peer), which is consistent with annotations. It does not disclose additional behavioral traits beyond that, but with annotations covering safety, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence that front-loads the action and resource ('Search message text') and includes the scope qualifier. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, all parameters are documented in the schema, and annotations cover safety. The description provides the necessary purpose and scope, making it complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so all four parameters are documented in the schema. The description adds minimal value, only reinforcing the peer omission behavior already stated in the schema ('Omit to search everywhere'). It does not compensate with extra semantic details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search message text' with a specific verb and resource, and distinguishes scope: 'inside one chat or across the whole account when no peer is given.' This differentiates it from sibling tools like history or list_chats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the two usage modes: with a peer (limit to a chat) or without (search across the account). It gives clear context for when to use the tool, though it does not explicitly name alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sendSend a messageAIdempotent
Send a message to a chat. This is visible to the recipient immediately and posts as you, so only send what was actually asked for.
| Name | Required | Description | Default |
|---|---|---|---|
| peer | Yes | A @username, numeric id, or 'me' for Saved Messages. | |
| text | Yes | The message body. Markdown is supported. | |
| silent | No | Deliver without a notification sound. | |
| reply_to | No | Message id to reply to. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false and destructiveHint=false, but the description adds important behavioral context: the message is visible immediately and posts as the user. This goes beyond the annotations by clarifying the side effects (permanent, attributed, immediate) and implies a need for caution. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-constructed sentence that front-loads the core purpose and appends a necessary caution. Every word earns its place; there is no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity—four parameters, two required, no output schema—the description covers the essential behavior: it sends a message that is immediately visible and attributed. It does not mention return values, but those are not required for correct invocation. It could be improved by naming siblings for differentiation, but that falls under usage guidelines.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all four parameters, so the schema already fully documents them. The description adds nothing about parameter meaning beyond what the schema provides, so it earns the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Send a message to a chat.' It specifies the resource (a chat message) and the verb (send), and adds the key distinction that it posts as the caller, separating it from forwarding or file-sending siblings. The immediate visibility note further sharpens what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear context—send when you need to deliver a message that is immediately visible and attributed to the user—but it does not explicitly mention alternatives like send_file or forward, nor does it state when not to use it. The warning 'only send what was actually asked for' is a usage guideline but not a routing guide to other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_fileSend a fileBIdempotent
Send a local file to a chat, with an optional caption.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Absolute path to the file to send. | |
| peer | Yes | A @username, numeric id, or 'me'. | |
| caption | No | Caption to attach. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states that it sends a file, providing no additional context about side effects, error conditions, or file handling. The annotations (readOnlyHint=false) already signal a write operation, so the description adds no extra behavioral information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the action and object. It is efficient and free of unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core intent and mentions the optional caption. It lacks explicit differentiation from the sibling 'send' tool, but for a simple file-sending operation, it provides sufficient context for an agent to understand the action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description repeats the parameter explanations from the schema verbatim. Since the schema covers all parameters at 100%, the description adds no new meaning beyond what the schema already provides, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Send' and the resource 'a local file to a chat', distinguishing it from the sibling 'send' tool which likely sends text messages. The scope is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly indicate when to use this tool versus the sibling 'send' tool, nor does it mention any conditions or exclusions. The distinction is only implied by the name and the word 'file'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
whoamiWho am IARead-onlyIdempotent
The Telegram account this session is signed in as. Call it first when it matters whose messages you are about to read or send.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior; the description reinforces that it simply reports the session's account without contradicting the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences deliver the purpose and usage guidance without unnecessary detail or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter identity lookup, the description sufficiently conveys what the tool returns and when to use it, even without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the baseline applies; the description adds no parameter-specific detail but none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly identifies the tool as returning the current Telegram account identity, and distinguishes it from message-oriented sibling tools by focusing on the session account.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call this tool first when account identity matters before reading or sending messages, providing a concrete usage condition.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
13 tool updates
v0.4.0- First observed
delete - First observed
download_media - First observed
edit - First observed
forward - First observed
get_chat - First observed
history - First observed
list_chats - First observed
mark_read - First observed
resolve - First observed
search - First observed
send - First observed
send_file - First observed
whoami
TDQS
Each tool has a clear, distinct purpose: send, send_file, and forward are differentiated by payload type and behavior; list_chats, get_chat, history, and search cover different levels of querying. No obvious overlaps or ambiguities.
Most tools follow a verb_noun pattern (send_file, list_chats, mark_read, download_media), but 'whoami' and 'history' deviate as standalone nouns. Overall the naming is consistent and predictable, with minor exceptions.
13 tools is within the typical 3-15 range and feels well-scoped for a messaging client. Each tool addresses a distinct part of the workflow without unnecessary bloat.
The core messaging lifecycle is covered: retrieving (list, get, history, search), sending (send, send_file, forward), mutating (edit, delete, mark_read), and identity (whoami). Some advanced features like pinning or archiving are absent, but the essential operations are complete.
Maintenance
Resources
Unclaimed servers have limited discoverability.
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