astral-bridge
The Astral Bridge server connects QQ and Telegram chat platforms to a fixed Astral Code app-server session. Key capabilities include:
Retrieve messages: Get recent stored messages (up to 100, with pagination), fetch a specific message by OneBot
message_id, or access the latest unread message batch for QQ and Telegram conversations.Search messages: Full-text search through stored QQ messages in a group or private conversation.
Get conversation state: Check bridge state details and message counts for a specific conversation.
Download media: Download stored image or file attachments to local cache and retrieve their file paths.
Send messages: Post to QQ groups or private chats with support for ordered mixed parts (text, @mentions, images) and replies. Also supports Telegram messaging, including voice via TTS.
Send files: Upload local files or URLs to QQ group or private chats.
Recall/delete messages and set reactions on QQ and Telegram.
QQ group administration: Manage members, handle join requests, change group settings, manage notices, files, and read group info.
Message routing: Route QQ and Telegram messages to a configured Astral app-server thread based on mentions, replies, trigger keywords, or always-trigger settings.
External webhooks: Accept and process generic external event webhooks, forwarding merged batches to Astral.
Web UI: A read-only interface to monitor connection status, routing, recent messages, and logs.
Local storage: Conversation history is stored in SQLite for later context lookups.
Enables the AI agent to communicate with QQ via the Astral Code app-server, allowing it to send and receive messages, manage conversation history, and handle media files within allowed QQ groups and private chats.
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., "@astral-bridgesend 'Hello from Astral' to group 123456"
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.
Astral Bridge
Astral Bridge connects QQ, through NapCat's OneBot v11 reverse WebSocket, and optionally Telegram, through the Telegram Bot API, to one long-lived Astral Code app-server session. It also exposes MCP tools so the agent can reply back to chat platforms, send files, mention people, recall/delete messages, and fetch recent conversation context when needed.
This project is intended for self-hosted personal or team automation. It is not affiliated with QQ, Tencent, NapCat, OneBot, Telegram, or Astral Code.
Features
Receive QQ private and group messages from NapCat over OneBot v11.
Receive Telegram private, group, supergroup, and channel-post messages through long polling.
Route every accepted message into one Astral app-server thread, either configured explicitly or auto-created on first startup.
Trigger group messages only when the bot is mentioned, replied to, or the chat is configured as always-trigger.
Trigger every message from configured private QQ or Telegram users/chats.
Store allowed conversation history locally in SQLite for later MCP lookups.
Include compact inbound context: platform, chat/group name/id, sender id, nickname, username/card, message id, reply id, trigger kind, unread count, and attachment metadata.
Support app-server
turn/steerwhen the current Astral thread already has an active turn.Expose Streamable HTTP or stdio MCP tools for QQ and Telegram replies, history, media, files, mentions, and replies to specific message ids.
Accept generic external event webhooks and forward them into the current Astral session.
Expose a read-only Web UI for connection status, routing, recent messages, recent conversations, and recent bridge logs.
Add a random 3-5 second delay before outbound QQ send actions.
Related MCP server: NapCat MCP Server
Requirements
Node.js 26 or newer. The bridge uses
node:sqlite.pnpm 10 or newer.
A running Astral Code app-server.
NapCat configured with OneBot v11 reverse WebSocket.
Optional: a Telegram bot token from BotFather if Telegram support is enabled.
Quick Start
pnpm install
cp examples/config.example.json config.json
pnpm dev -- --config ./config.jsonBuild for production:
pnpm build
pnpm start -- --config ./config.jsonPoint NapCat's OneBot v11 reverse WebSocket to:
ws://127.0.0.1:6701/onebot/v11/wsIf the bridge is running in Docker or on another host, replace the host and port with the address reachable from NapCat, for example:
ws://bridge:6701/onebot/v11/wsConfiguration
Start from examples/config.example.json:
{
"onebot": {
"host": "127.0.0.1",
"port": 6701,
"path": "/onebot/v11/ws",
"accessToken": null,
"actionTimeoutMs": 10000
},
"mcp": {
"transport": "stdio",
"host": "127.0.0.1",
"port": 6710,
"path": "/mcp"
},
"astral": {
"appServerUrl": "ws://127.0.0.1:4222",
"authToken": null,
"threadId": "auto",
"cwd": null,
"modelConfigPath": null,
"modelProvider": null,
"model": null,
"includeImageInputs": false,
"rotateThreadOnStart": false
},
"qq": {
"enabled": true,
"botUserId": "REPLACE_WITH_BOT_QQ",
"allowedGroupIds": ["REPLACE_GROUP_ID"],
"alwaysTriggerGroupIds": [],
"allowedPrivateUserIds": ["REPLACE_USER_ID"],
"triggerKeywords": ["astral", "bot"],
"recordUntriggered": true
},
"telegram": {
"enabled": false,
"botToken": "REPLACE_WITH_TELEGRAM_BOT_TOKEN",
"botUsername": "REPLACE_WITH_TELEGRAM_BOT_USERNAME",
"allowedChatIds": ["REPLACE_TELEGRAM_CHAT_ID"],
"alwaysTriggerChatIds": [],
"triggerKeywords": ["astral", "bot"],
"recordUntriggered": true,
"pollTimeoutSeconds": 25,
"pollIntervalMs": 1000,
"apiBaseUrl": "https://api.telegram.org"
},
"tts": {
"enabled": false,
"protocol": "openai_speech",
"apiKey": null,
"baseUrl": "http://127.0.0.1:8765/v1",
"model": "mlx-community/Qwen3-TTS-12Hz-0.6B-Base-bf16",
"voice": null,
"format": "mp3",
"language": "Chinese",
"referenceAudioPath": "/absolute/path/on/tts-server/atri.wav",
"referenceText": "参考音频中准确说出的文字",
"timeoutMs": 60000
},
"embedding": {
"enabled": false,
"baseUrl": "http://127.0.0.1:8766/v1",
"apiKey": null,
"model": "qwen3-embedding-0.6b",
"dimensions": 1024,
"batchSize": 32,
"timeoutMs": 60000,
"queryInstruction": "Given a user query about instant-message history, retrieve messages that answer the query or express the same meaning."
},
"externalEvents": {
"enabled": true,
"path": "/api/events",
"authToken": "REPLACE_WITH_EVENT_API_TOKEN",
"maxBodyBytes": 65536,
"debounceMs": 2000,
"maxBatchEvents": 20,
"maxBatchBodyChars": 6000
},
"storage": {
"dbPath": "./data/astral-bridge.db",
"mediaDir": "./media",
"downloadMedia": false
}
}Environment overrides:
Variable | Description |
| Path to the JSON config file. |
| Astral app-server WebSocket URL. |
| Bearer token for Astral app-server. |
| Optional fixed Astral thread/session id. Leave empty or set |
| Auto-managed mode only. Set |
| Optional Astral |
| Optional static provider override when |
| Optional static model override when |
| Enable the QQ/NapCat channel and expose QQ MCP tools. |
| Bot QQ user id. |
| Comma-separated allowed group ids. |
| Comma-separated group ids where every non-bot message is forwarded to Astral. |
| Comma-separated allowed private user ids. |
| Comma-separated QQ trigger keywords. Any allowed group/private message containing one keyword, case-insensitively, is forwarded to Astral. |
| Enable Telegram long polling. |
| Telegram bot token from BotFather. |
| Optional bot username, without or with |
| Comma-separated Telegram |
| Comma-separated Telegram chat ids where every non-bot message is forwarded to Astral. |
| Comma-separated Telegram trigger keywords. Any allowed chat message containing one keyword, case-insensitively, is forwarded to Astral. |
| Store non-triggering Telegram messages from allowed chats. |
| Telegram |
| Delay after a failed Telegram poll before retrying. |
| Enable TTS-backed QQ/Telegram voice message tools. |
|
|
| Optional API key. Required by |
| TTS API base URL, including |
| TTS model id sent to the configured endpoint. |
| Configured bot voice, hidden from MCP tool schemas. |
| Audio response format: |
| Optional language hint sent as |
| Optional reference audio path as seen by the TTS server. |
| Exact transcript of the reference audio; must be configured together with its path. |
| TTS request timeout in milliseconds. |
| Enable asynchronous message embeddings and semantic/hybrid |
| OpenAI-compatible embeddings API base URL, including |
| Optional bearer token for the embeddings API. |
| Embedding model id sent to the configured endpoint. |
| Stored vector dimensions. Changing this rebuilds the vector index. |
| Maximum messages embedded in one background request. |
| Embedding request timeout in milliseconds. |
| Retrieval instruction prepended to semantic search queries. |
|
|
| Enable or disable the external event API. |
| External event API path, default |
| Optional bearer token required by the external event API. |
| Window used to merge attention-worthy external events before forwarding to Astral. |
| Maximum external events included in one merged Astral turn. Extra events in the same window are counted and omitted. |
| Maximum merged event body characters sent to Astral. Longer batches are truncated. |
When astral.threadId / ASTRAL_BRIDGE_THREAD_ID is empty or auto, bridge creates one
Astral thread on first use and stores the id in SQLite store_meta. To rotate an
auto-managed thread manually, call POST /api/astral/thread/rotate with the same bearer
token as the external event API. If a turn is currently active, the endpoint returns 409
instead of interrupting it.
recordUntriggered controls whether non-triggering messages from allowed conversations
are stored. Keeping it enabled lets the agent fetch surrounding context without forwarding
every group message into Astral. For QQ this also stores member-to-member poke notices in
allowed groups; only pokes targeting the bot trigger an Astral turn.
Telegram uses long polling. On startup the bridge calls deleteWebhook so Telegram will
allow getUpdates. Send /chatid to the bot in a private chat, group, supergroup, or
topic to get the exact chat_id; this command works even before the chat is allowlisted.
All other Telegram interaction requires the chat id to be present in
telegram.allowedChatIds or telegram.alwaysTriggerChatIds.
Web UI
When HTTP MCP is enabled, open:
GET /uiThe dashboard polls GET /api/dashboard/state and shows NapCat/Astral connection status,
the active Astral turn id when one is running, configured routing, external event API
status, recent conversations, recent stored messages, and recent bridge logs.
Astral MCP Setup
For stdio MCP, build first and point Astral at the compiled entrypoint:
[mcp_servers.bridge]
command = "node"
args = ["/path/to/astral-bridge/dist/index.js", "--config", "/path/to/astral-bridge/config.json"]Use node directly instead of a package-manager wrapper. stdio MCP requires stdout to
contain only JSON-RPC messages.
For container or multi-process deployments, run HTTP MCP:
{
"mcp": {
"transport": "http",
"host": "0.0.0.0",
"port": 6710,
"path": "/mcp"
}
}Then configure Astral:
[mcp_servers.bridge]
url = "http://bridge:6710/mcp"The bridge exposes both QQ and Telegram tools from the same MCP endpoint, so register it
once. Tool names remain platform-specific, for example
mcp__bridge__qq_send_group_message and mcp__bridge__telegram_send_message.
QQ tools are registered only when qq.enabled is true, Telegram tools only when
telegram.enabled is true, and voice tools only when tts.enabled is true.
MCP Tools
Shared Tool | Purpose |
| Run isolated read-only JavaScript over QQ/TG history with |
query_messages is intended for complex recall and analysis rather than ordinary recent-message
lookups. Its code argument is an async JavaScript function body that must return JSON. Each
invocation runs in a separate process against a read-only SQLite connection and is terminated
after 30 seconds. Helper limit values are defaults rather than hard maxima; Astral applies its
normal MCP-output context limit after the bridge returns the result.
return search("电路图", { platform: "qq", context_limit: 2 });When embeddings are enabled, search() defaults to hybrid FTS5 plus semantic recall. Semantic
and hybrid searches are asynchronous, while explicit lexical searches retain the synchronous
FTS5 path:
return await search("上次谁说显卡坏了", { mode: "hybrid", platform: "qq", context_limit: 2 });For custom KNN joins, use await embed(text) and bind the returned float32 vector directly to
sql(). The vector is never printed into the tool result:
const vector = await embed("串流画面问题");
return sql(
"SELECT m.id AS row_id, m.text, e.distance FROM message_embeddings e JOIN messages m ON m.id = e.message_row_id WHERE e.embedding MATCH ? AND e.k = ? ORDER BY e.distance",
vector,
20,
);Message writes and FTS5 updates never wait for the embedding service. New and historical
messages are queued in SQLite and indexed in the background. If the local model is unavailable,
semantic/hybrid calls return a clear error and mode: "lexical" remains available.
Use schema() from inside the query when exact table fields are needed. Use sql() only for
joins, grouping, time buckets, and other shapes not covered naturally by the higher-level helpers.
QQ Tool | Purpose |
| Send a group message with text, images, ordered parts, mentions, or a reply target. |
| Send a private message with text, images, ordered parts, or a reply target. |
| Generate TTS audio and send it as a real QQ group voice message. |
| Generate TTS audio and send it as a real QQ private voice message. |
| Upload a local file or URL to a QQ group. |
| Upload a local file or URL to a QQ private chat. |
| Return the unread batch counted by the latest inbound Astral prompt. |
| Return recent stored messages for one group or private conversation. |
| Return one stored message by OneBot |
| Expand every node in one stored, allowlisted QQ merged-forward message without persisting or downloading its contents. |
| Return bridge state and counts for one conversation. |
| Download a stored attachment, or one attachment selected by a merged-forward |
| React to a stored QQ group message by OneBot |
| Explain grouped QQ administration tools and actions. |
| Kick, mute/unmute, set admin, set card, set special title, or list muted members. |
| Read or handle group join/invite requests. |
| Change group name/avatar, whole-group mute, or make the bot leave the group. |
| Recall messages, manage essence messages, check @all quota, or mark group read. |
| Send, list, or delete group notices. |
| Manage group files and folders. |
| Read group, member, and honor information. |
Telegram Tool | Purpose |
| Send text with ordered text/mention parts, optional reply target, and optional topic thread id. |
| Send structured rich text with Telegram Rich Message HTML or Markdown. |
| Send a local path, Telegram |
| Generate TTS audio and send it as a real Telegram voice message. |
| Delete/recall a message when Telegram permissions allow it. Requires |
| React to a Telegram group or private message with one standard reaction emoji; the tool description lists the allowed emoji values. |
| Return the unread batch counted by the latest inbound Astral prompt. |
| Return recent stored messages for one Telegram chat. |
| Return one stored Telegram message by |
| Return bridge state and counts for one Telegram chat. |
| Download a stored Telegram attachment into the local media cache. |
Group Administration
Group administration tools are grouped to keep the MCP tool list small. Call
qq_group_admin_help to discover action names and required fields. Disbanding groups is
intentionally not implemented; leave_group only makes the bot leave the group.
All group-specific administration tools reject group_id values outside
qq.allowedGroupIds when that allowlist is configured. Actions that mutate group state
require confirm: true; use that only after the user explicitly asks for the operation.
Mentions, Images, and Replies
Use parts when a group message needs exact ordering of text, mentions, and images:
[
{ "type": "text", "text": "请 " },
{ "type": "at", "user_id": "TARGET_QQ" },
{ "type": "text", "text": " 看一下 " },
{ "type": "image", "file": "/workspace/result.png" }
]Reply to a specific QQ message by passing reply_to_message_id with the OneBot
message_id from the inbound prompt or one of the history tools.
Images in outbound messages use OneBot image segments. Non-image files use
NapCat-compatible upload_group_file and upload_private_file actions.
QQ merged-forward messages remain opaque in inbound prompts and history until the agent calls
qq_get_forward_messages. The tool returns every nested node in depth-first order. To fetch one
internal image, file, voice, or video afterward, pass the outer message_id, the returned
forward_node_path, and its zero-based attachment_index to qq_download_media. Forwarded
children are never added to ordinary history, FTS, or embedding indexes.
Telegram text messages use ordered parts for mentions:
[
{ "type": "text", "text": "请 " },
{ "type": "mention", "username": "alice" },
{ "type": "text", "text": " 看一下;也同步给 " },
{ "type": "mention", "user_id": "123456789", "text": "Bob" }
]Use telegram_send_rich_message when a Telegram reply needs structured formatting
such as headings, lists, tables, collapsible details, code blocks, or formulas. Pass
exactly one of html or markdown:
{
"chat_id": "-1001234567890",
"html": "<h2>Summary</h2><ul><li>Done</li><li>Next step</li></ul>",
"reply_to_message_id": "123",
"message_thread_id": "456"
}For Telegram files, call telegram_send_file for images and non-images alike. This sends
through Telegram sendDocument, preserving the original file quality. Telegram rich
message media blocks are intended for HTTP/HTTPS URLs; local /workspace and
/app/media files should still be sent with telegram_send_file:
{
"chat_id": "-1001234567890",
"file": "/workspace/result.png",
"caption": "结果图",
"reply_to_message_id": "123",
"message_thread_id": "456"
}Message Routing
The bridge only forwards messages from configured QQ targets or Telegram chat ids:
Group messages: forwarded when the bot is at-mentioned or the message replies to a bot message.
Keyword messages: in any allowed QQ/Telegram group or private chat, messages containing any configured trigger keyword are forwarded. Keyword matching is case-insensitive.
Always-trigger group messages: for group ids in
qq.alwaysTriggerGroupIds, every non-bot message is forwarded, even without an @mention or reply.Private messages: forwarded for every message from configured private users.
Other allowed conversation messages: optionally stored when
recordUntriggeredis true, but not forwarded to Astral.Telegram
/chatid: always answered directly so you can discover the current Telegramchat.idbefore editing the allowlist.Telegram group/supergroup/channel messages: forwarded when the bot is mentioned, the message replies to a bot message, or the chat id is in
telegram.alwaysTriggerChatIds.Telegram private messages: forwarded for every message from configured private chat ids.
/stop: in any allowed QQ/Telegram group or private chat, interrupts the active Astral turn and replies in the same conversation.
Every forwarded turn includes conversation_unread_count, the number of stored messages
in the same group/private conversation since the previous Astral
prompt, including the current trigger message. The agent can call qq_get_unread_messages
or telegram_get_unread_messages when that context is useful; it does not need to call it
for every message.
External Event API
When HTTP MCP is enabled, the same HTTP server can accept generic external events:
GET /api/events/schemaReturns a machine-readable OpenAPI 3.1 schema with examples and curl usage.
POST /api/events
Authorization: Bearer REPLACE_WITH_EVENT_API_TOKEN
Content-Type: application/json{
"source": "minecraft:survival-main",
"event_type": "player_join",
"title": "Player joined",
"body": "Steve joined the server",
"actor": { "id": "uuid", "name": "Steve" },
"metadata": { "world": "world", "x": 120, "y": 64, "z": -33 }
}The bridge queues attention-worthy events, merges short bursts into one bounded Astral
turn, and submits that merged event to the current Astral thread using the same queue as QQ
messages. Set wants_agent_attention to false to validate and accept an event without
forwarding it into Astral. Batching is controlled by externalEvents.debounceMs,
externalEvents.maxBatchEvents, and externalEvents.maxBatchBodyChars.
Request fields:
Field | Required | Description |
| Yes | System or integration name, such as |
| No | Event kind. Defaults to |
| No | Short title. |
| No | Main event text. |
| No | Severity label. Defaults to |
| No | Entity that caused the event. |
| No | Structured event details. |
| No | Optional stable key supplied by the caller. |
| No | ISO timestamp, Unix seconds, or Unix milliseconds. |
| No | Defaults to |
| No | Caller-supplied event id. A UUID is generated when omitted. |
Successful requests return 202 Accepted with { ok, accepted_for_astral, event }.
Unauthorized requests return 401 when externalEvents.authToken is configured.
Astral App-Server Behavior
The bridge talks to Astral app-server over WebSocket and uses:
initializethread/resumeturn/startturn/steerwhen the current thread already has an active turn
When starting a turn, the bridge requests approvalPolicy = "never" and
sandboxPolicy = { type = "dangerFullAccess" }. If you use this mode, isolate Astral at
the container, VM, or host level and only mount directories you are willing to expose.
Server approval requests for command execution and file changes are canceled by default. QQ sending should happen through the MCP tools and Astral MCP tool approval settings, not through the bridge approving arbitrary app-server actions.
Docker and OrbStack
The generic bridge image is defined by Dockerfile.
OrbStack deployment templates live under deploy/orbstack. They include:
bridge: OneBot reverse WebSocket plus Streamable HTTP MCP.astral-code: an Ubuntu-based Astral app-server runtime with mapped config, binary, source, workspace, and build cache directories.napcat: NapCat Docker service.
Copy deploy/orbstack/.env.example to .env, fill in your local values, and read
the Chinese deployment guide at deploy/orbstack/README.md before running the compose
stack. It covers required QQ/Telegram/Astral settings, persistent volumes, memory storage,
and the memory phase2 sandbox option.
Security Notes
Do not commit real QQ ids, app-server tokens, API keys, NapCat WebUI tokens, SQLite databases, downloaded media, or local config files.
Bind services to loopback unless you intentionally need LAN access.
The app-server danger-full-access mode is powerful. Use a dedicated container or host account and mount only the workspace/config directories needed by the agent.
Review allowed groups and private users before exposing the bot to busy chats.
Development
pnpm install
pnpm typecheck
pnpm buildProject layout:
src/ Bridge source
examples/ Example JSON config
deploy/orbstack/ Self-hosted OrbStack deployment template
data/ Runtime SQLite state, ignored by git
media/ Runtime media cache, ignored by gitAcknowledgements
The design of query_messages was inspired by
Obelisk and its agent-first approach to retrieval:
give the agent a programmable query surface over a local SQLite index, then
let the agent decide how to search, inspect context, and follow the evidence. Thank you for
showing how much more capable retrieval becomes when the agent owns the query plan.
License
Licensed under the Apache License, Version 2.0. See LICENSE.
Available Tools
10 toolsqq_download_mediaC
Download a stored QQ image/file attachment to the local media cache and return its path.
| Name | Required | Description | Default |
|---|---|---|---|
| attachment_id | No | ||
| message_id | No | ||
| attachment_index | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description should fully disclose behavioral traits. It mentions downloading to local cache and returning a path, but does not specify side effects (e.g., overwrites), permission needs, or what happens if the attachment does not exist.
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, front-loaded sentence with no redundant words. Every part contributes to stating the tool's core action and result, which is ideal for conciseness.
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 absence of annotations, output schema, and parameter descriptions, the description is too sparse. It does not cover prerequisites, return value format, or parameter semantics, making it incomplete for secure or correct use.
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?
With 0% schema description coverage, the description was expected to explain the three parameters (attachment_id, message_id, attachment_index). It fails to do so, leaving their roles and constraints entirely undocumented.
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 'download' and the resource 'stored QQ image/file attachment', indicating its function. However, it does not explicitly differentiate from sibling tools like qq_send_group_file or qq_get_message, which might also involve attachments.
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 no guidance on when to use this tool versus alternatives. It lacks context about prerequisites, such as needing a message_id, or situations where other tools would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_get_conversation_stateC
Get bridge state for a QQ conversation.
| Name | Required | Description | Default |
|---|---|---|---|
| target_type | Yes | ||
| target_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like whether the tool is read-only, requires authentication, or has side effects. It simply states the operation, leaving the agent unaware of implications.
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, which is concise but lacks essential details. It earns a middling score because while brevity is valued, the content is too sparse.
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 lack of output schema and annotations, the description should provide more context about what 'bridge state' entails and how the output can be used. It fails to make the tool self-contained.
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 0% description coverage, and the description does not explain what 'target_type' or 'target_id' represent beyond their names. The agent gets no additional context to properly populate parameters.
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 'Get' and the resource 'bridge state for a QQ conversation', making the tool's purpose unambiguous. It distinguishes from sibling tools like qq_get_message by specifying 'bridge state', which is unique.
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 no guidance on when to use this tool versus alternatives, such as when to retrieve conversation state instead of messages. No prerequisites or context hints are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_get_messageC
Get one stored QQ message by OneBot message_id.
| Name | Required | Description | Default |
|---|---|---|---|
| message_id | Yes | ||
| target_type | No | ||
| target_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only says 'get'. It fails to disclose read-only nature, return structure, error handling, or whether the message must be previously stored by the bot. Minimal transparency.
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 wasted words. It is front-loaded with the verb and object. However, brevity comes at the cost of missing critical 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?
Given three parameters and no output schema, the description is severely incomplete. It omits return format, optional parameter roles, and any preconditions, leaving the agent underinformed for correct invocation.
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 0%; the description adds no meaning to parameters. It ignores target_type and target_id, leaving their purpose ambiguous given only message_id is required. The agent has no clue how to use optional params.
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 it retrieves a stored QQ message by OneBot message_id, which distinguishes it from sibling tools that list or search messages. However, it could be more specific about the scope (e.g., 'single 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?
No guidance is provided on when to use this tool versus alternatives like qq_search_messages or qq_get_recent_messages. The agent receives no context about prerequisites or preferred scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_get_recent_messagesC
Get recent stored QQ messages for a group or private conversation.
| Name | Required | Description | Default |
|---|---|---|---|
| target_type | Yes | ||
| target_id | Yes | ||
| limit | No | ||
| before_message_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states 'Get recent stored QQ messages' without explaining pagination (using before_message_id), ordering, default limit, or whether media is included. The minimal description leaves critical behavioral traits unspecified.
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 with no wasted words, but its brevity comes at the cost of completeness. It does not earn its place because it omits essential information for tool invocation.
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?
With no output schema, no annotations, and 0% parameter description coverage, the description is severely incomplete. It fails to explain pagination, error handling, rate limits, or response format, leaving an AI agent underinformed.
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 0%, and the description adds no parameter details. Properties like target_type, target_id, limit, and before_message_id are not explained. The description does not help an agent understand parameter roles beyond their names and types.
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?
Description clearly states verb ('get'), resource ('recent stored QQ messages'), and context ('group or private conversation'). It matches the target_type enum. However, it does not explicitly differentiate from sibling tools like qq_get_message or qq_get_unread_messages, so clarity is slightly reduced.
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 on when to use this tool versus alternatives. For example, it does not mention that this tool fetches stored history while qq_get_unread_messages filters unread, or that qq_search_messages is for searching. The description lacks usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_get_unread_messagesB
Get the current unread batch for a group or private conversation. This returns the messages counted by the latest conversation_unread prompt.
| Name | Required | Description | Default |
|---|---|---|---|
| target_type | Yes | ||
| target_id | Yes | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions it returns 'messages counted by the latest conversation_unread prompt', which is vague and jargon-heavy. It does not clarify whether the tool is read-only, if it marks messages as read, or any side effects like rate limits or authentication requirements.
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 only two sentences, focusing on the core function. However, the second sentence is somewhat redundant and uses unclear phrasing ('conversation_unread prompt'), slightly reducing clarity. Overall, it is concise but could be more efficient.
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 complexity of unread message retrieval, no output schema, and sibling tools, the description is incomplete. It does not describe the return format (e.g., list of messages, IDs, or full objects), pagination, or prerequisites. This leaves agents uncertain about how to use the response or how the tool fits with related functionality.
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 0%, so the description must compensate. It relates target_type to group/private conversation and implies target_id identifies the conversation, but it does not explain the limit parameter (its default, meaning, or effect). The description adds minimal value beyond the schema itself, leaving parameter semantics largely unexplained.
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 it gets the current unread batch for a group or private conversation, specifying the verb 'get' and resource 'unread messages'. This distinguishes it from siblings like qq_get_recent_messages, which retrieves all recent messages, and qq_get_message, which gets a specific 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 implicitly indicates it is for unread messages, but it does not explicitly state when to use this tool versus alternatives like qq_get_recent_messages or qq_search_messages. No when-not-to-use guidance is provided, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_search_messagesB
Search stored QQ text messages in a group or private conversation.
| Name | Required | Description | Default |
|---|---|---|---|
| target_type | Yes | ||
| target_id | Yes | ||
| query | Yes | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for disclosing behavioral traits. It only states the basic purpose and fails to describe important behaviors such as search algorithm (e.g., exact match, partial match), case sensitivity, handling of no results, authentication requirements, or pagination. This leaves significant uncertainty for an agent.
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 of 10 words, extremely concise and front-loaded with the key action and scope. Every word is necessary; there is no superfluous information. It is the model of conciseness.
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 has 4 parameters (3 required), no output schema, and no annotations, the description is too terse. It omits critical context such as the format of search results (list of message IDs? full message objects?), error behavior, rate limits, and how the search interacts with QQ's storage (e.g., date range? all history?). Sibling tools like 'qq_get_message' suggest there might be message IDs, but without output schema or further detail, an agent cannot reliably interpret 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?
Schema description coverage is 0%, so the description must compensate. It does not explain the semantics of individual parameters: target_id format (e.g., numeric ID or string?), query syntax (free text, exact match?), or limit behavior. It only implies via the description that target_type and target_id specify the conversation, which is already clear from the schema. This adds minimal value beyond the schema.
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 searches stored QQ text messages and specifies the scope (group or private conversation). The name 'qq_search_messages' aligns with the action, and it is distinguishable from sibling tools like 'get_message' or 'get_recent_messages' which retrieve specific messages or lists rather than performing a search.
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 vs alternatives. There is no mention of prerequisites, limitations, or when not to use it. The description lacks contextual cues that help an agent decide to invoke this over other message retrieval tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_send_group_fileC
Upload a local file or URL to a QQ group using NapCat's OneBot-compatible file action.
| Name | Required | Description | Default |
|---|---|---|---|
| group_id | Yes | ||
| file | Yes | ||
| name | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description lacks details on behavioral traits such as authorization requirements, side effects, error handling, or limitations on file size/types. With no annotations, the description should fully disclose these, but it does not.
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?
Single sentence, no redundancy, efficiently states the action. Could be improved by front-loading key constraints, but acceptable.
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?
Tool has 3 parameters, no output schema, and no annotations. Description does not explain return values, error conditions, parameter formats, or operational limitations. Incomplete for effective agent use.
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 has 0% coverage, so description must compensate. It implies file can be a local path or URL, but does not specify format for group_id or the name parameter. The optional name is mentioned but not explained. Adds minimal semantic value.
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 it uploads a local file or URL to a QQ group, using a specific compatible action. It distinguishes the target (QQ group) from siblings like qq_send_private_file, but does not explicitly contrast with qq_send_group_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?
No guidance on when to use this tool versus alternatives like qq_send_group_message or qq_send_private_file. Missing context for when uploading a file is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_send_group_messageB
Send a QQ group message. Supports exact ordered parts for mixed text, @mentions, and images.
| Name | Required | Description | Default |
|---|---|---|---|
| group_id | Yes | ||
| message | No | ||
| images | No | ||
| parts | No | ||
| reply_to_message_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description only discloses that it sends a message and supports ordered parts, but lacks details on mutation behavior, failure handling, auth requirements, or rate limits, leaving significant gaps.
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 short sentences with no wasted words; the purpose is front-loaded and the feature support is concisely stated.
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?
Despite 5 parameters, no annotations, and no output schema, the description is minimal; it does not explain return values, usage of individual params beyond parts, or prerequisites for sending group messages, making it incomplete for an agent.
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 has 0% description coverage; the description adds some meaning to the 'parts' parameter (ordered types) but fails to explain other parameters like group_id, message, images, or reply_to_message_id, so it only partially compensates.
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 'QQ group message', and mentions support for mixed text, @mentions, and images, distinguishing it from sibling tools like qq_send_private_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 implies usage for sending group messages but does not explicitly state when not to use it or provide alternatives; usage guidance is implied but not thorough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_send_private_fileB
Upload a local file or URL to a QQ private chat using NapCat's OneBot-compatible file action.
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | ||
| file | Yes | ||
| name | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It mentions accepting both local files and URLs, which is useful, but lacks details on behavioral traits such as file size limits, whether URL downloads are performed server-side, or whether the operation is idempotent. As an upload action, it likely creates a resource, but this is implicit.
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, front-loaded sentence that immediately conveys the primary action and target. It is concise and avoids fluff, though it sacrifices important parameter details. The structure is efficient for the purpose it serves.
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 low parameter coverage (0%), no output schema, and no annotations, the description is incomplete for an agent to safely and correctly invoke this tool. Key missing items include return value, error scenarios, prerequisites (e.g., logged-in user), and file path requirements. The description only covers the basic 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?
Schema description coverage is 0%. The description does not elaborate on any of the three parameters (user_id, file, name). While 'file' is hinted at via 'local file or URL', there is no explanation of user_id format, the purpose of optional name, or constraints like supported file types. The agent must infer from parameter names alone.
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 explicitly states the action ('Upload a local file or URL') and the target resource ('QQ private chat'). It distinguishes from siblings by specifying 'private' as opposed to group file sending, and also mentions the underlying protocol ('NapCat's OneBot-compatible file action'), providing clear purpose.
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 clearly indicates use in private chats via the phrase 'to a QQ private chat', which helps differentiate from group file sending (sibling qq_send_group_file). However, it does not provide explicit when-not-to-use guidance or compare with sending private messages (qq_send_private_message), which may cause ambiguity for agents unaware of file vs message distinction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
qq_send_private_messageB
Send a QQ private message. Supports exact ordered text/image parts and replying to a message id.
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | ||
| message | No | ||
| images | No | ||
| parts | No | ||
| reply_to_message_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions support for ordered parts and replies but omits critical behavioral details like side effects, rate limits, authentication requirements, or what happens if the user is offline. The transparency is minimal beyond basic functionality.
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 at two sentences, with the first sentence stating the core purpose. It is front-loaded and contains no redundant information, though a slightly more structured layout could improve readability.
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 5 parameters (one required), 0% schema coverage, and no output schema, the description is insufficient. The tool supports complex features like ordered parts and replies, but the description does not explain how to use the 'parts' array, image formats, or reply functionality in enough detail for an agent to use 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 description coverage is 0%, but the description only references 'parts' and 'reply_to_message_id' indirectly. Required parameter 'user_id' and optional 'message', 'images', and nested 'parts' structure are not explained. The description adds little meaning beyond parameter names.
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' and the resource 'QQ private message', and highlights specific features (ordered text/image parts, replying). It effectively distinguishes from sibling tools like qq_send_group_message and qq_send_private_file.
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 sending private messages with ordered parts or replies, but lacks explicit guidance on when to use this over alternatives, such as qq_send_private_file for file-only messages. No exclusion criteria or prerequisites are mentioned.
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.
10 tool updates
v0.1.0- First observed
qq_download_media - First observed
qq_get_conversation_state - First observed
qq_get_message - First observed
qq_get_recent_messages - First observed
qq_get_unread_messages - First observed
qq_search_messages - First observed
qq_send_group_file - First observed
qq_send_group_message - First observed
qq_send_private_file - First observed
qq_send_private_message
TDQS
Scored across 10 tools
Each tool targets a distinct operation: download media, retrieve various message types, send messages/files to group/private, and check conversation state. No ambiguity between tools.
All tools follow a consistent `qq_verb_noun` snake_case pattern, using clear verbs like download, get, send, search and specific objects like media, message, group_file, private_message.
10 tools is well-scoped for a messaging bridge, covering message retrieval, sending, file uploads, and state queries without superfluous or missing functionality.
Core message lifecycle is covered: read, search, send (text/files) for both group and private. Minor gaps like deleting messages or listing conversations exist but are acceptable for a bridge focused on message relay.
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