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superbot.gg · your own AI agent

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superbot is your own AI agent: anything you can do on your computer, it can do, fast.

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Status
Unhealthy
Uptime
0.0% over the last 24 hours
OAuth
Works in Glama
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
Repository
superbot-gg/superbot-mcp
GitHub Stars
0
ChatGPT
–
Claude
–

TDQS

A3.7/5.0

Scored across 1 tool

Disambiguation5/5

There is only one tool, so there is no possibility of selecting the wrong one or confusing overlapping purposes. All routing happens inside the tool via intent/use_case, which is a dispatch concern rather than a disambiguation concern.

Naming Consistency5/5

A single tool named 'superbot' matching the server name cannot violate any naming pattern. There is no mixed convention or inconsistent verb style to penalize.

Tool Count3/5

One tool is a deliberate meta-agent design, but cramming dozens of distinct capability families (fax, email, calendar, browser automation, media generation, code search) into a single opaque intent string is on the thin side of the range and limits typed parameters and discoverability. It is borderline rather than clearly wrong for an 'everything agent' server.

Completeness4/5

Because every request routes through one generalist agent, there is no obvious dead end in the capability surface—CRUD-ish actions for mail, calendar, Notion, GitHub, automations and more are all reachable. The only gap is the absence of direct, structured operations with explicit inputs for users who need deterministic control rather than intent-based dispatch.

Available Tools

1 tool
superbotSuperbot: fax, calls, texts, Gmail drafts, calendar, web search, documents, mediaBInspect

Superbot can: send a fax (outbound only); place a phone call and report back what they said; send a text message (SMS); post a message to a Slack channel or DM someone; draft or send email from the user's Gmail; create a calendar event, invite people and check when the user is free; save a file to Google Drive; search, read and create Notion pages; schedule a recurring task or automation; search the web and get today's news headlines; read a web page or link, including one that needs JavaScript; search scholarly papers and GitHub repositories; open a page in a browser, click, type and take a screenshot; convert currencies, quote stock and crypto prices, get the weather and the time in any city; generate an image or picture; generate a short video, speech, music or a 3D model; build a spreadsheet, document, deck or PDF and pull text and tables out of a PDF; search flights between two airports; find UI design references, shadcn components and icons; find and install an MCP server. Superbot can also: check your GitHub profile, public repos and notifications; list, pause, change or delete your automations; crawl a few pages of a site; summarize a Wikipedia article; find licensed photos of real things with a credit line; search flights between two airports and compare offers; check where a flight stands from the confirmation in your calendar; look up UI design rules for a web, mobile or desktop surface; find reference screenshots of real apps and sites; search open-source icons. Process a user request: send it as plain text in intent and get a finished result back to hand to the user. The superbot agent answers it, with its tools and adapter catalog where they help; to find an adapter for a described task, pass use_case instead of intent (the search also returns any access method the knowledge store has proven for that task, as data to test). Answers are generated by an AI and can make mistakes. This is the only tool. Long requests: a call may return a processing answer with a request_id: tell the user it is being worked on, then call again with that request_id to fetch the finished answer. Send context (string) with the surrounding conversation when available: what the user is trying to solve, recent turns, issues hit so far; the backend composes a much better answer with it than from a compacted intent. When the answer needs one specific decision from the user before the work can carry on, it ends with a decision card: what got done, then a fenced block whose info string is superbot-embed and whose body is one JSON envelope of kind "decision" (a one-sentence question and 2 to 5 options), which the host draws as tappable choices and answers back as a "Picked: ()" user turn carrying the card and option id on a trailing line. When the work continues after the answer (a job started, a request that came back still processing), the answer ends with a monitor card the host keeps refreshing through check turns ending in "(monitor card : check)", which are answered with only the updated card. When the answer surfaces a message found in a mailbox, it ends with an email card, and a request to write, rewrite, polish, shorten, reformat, send or reply to one ends with an email_draft card (always state "draft" at first; mailbox and to may be omitted when the user named neither, and the host then offers Copy and Open in Mail instead of Send) that only sends when the host's own Send tap comes back as "(email_draft card : send)" with the exact edited draft, answered with only the updated fence.

NameRequiredDescriptionDefault
argsNoThe adapter's own input fields as ONE object, named as its input_schema or a search hit's `args` lists them. Fields placed at the top level of this call, beside `adapter`, are not read.
codeNo
modeNo
slugNoRead ONE adapter's definition (its input_schema: every field, its type, which are required) without running it.
callsNo
intentNo
wait_sNo
adapterNoThe adapter to run, by the slug a use_case search returned. Its own fields go in `args`.
composeNo
contextNo
triggerNo
researchNo
use_caseNoDescribe the task in the user's own words to find an adapter for it, instead of sending intent. Examples: 'send a fax', 'call a business and ask a question', 'text a phone number', 'draft an email in Gmail', 'create a calendar event', 'search the web for news'.
host_mcpsNo
commit_askNoThe ask_id a commit_pending result named. After the user approves it on their devices, a call with only this field runs that exact committed call once.
request_idNo
session_idNoThe session id returned in a prior response from this same tool, to continue that conversation and reuse its session-scoped step-up credentials. Omit to start a new session.
commit_grantNoThe commit grant (cgr_…) read from an approved commit ask's poll, for one run of a committing adapter. Single use; only the user's own approval mints one.
known_fieldsNoExtra hints for a use_case search (named entities, constraints, the service meant): a phrase, an object of named values, or a list of phrases.
inputResponsesNoAlias of input_responses for non-string values, answering the same prior result's step-up ask: same adapter-slug keys, but each value may be a token string or an object carrying {token} / {content:{token}}.
input_responsesNoThe caller's answers to a credential step-up ask that arrived inside a prior call's own result (SEP-2322 MRTR), not a separate tool: keyed by adapter slug (or the legacy 'token' key), each value the credential token as a plain string.

TDQS

B3.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and does disclose important behavior: answers are AI-generated and may make mistakes, long requests may return a processing answer with request_id, and host-side cards govern decisions, monitoring, email drafts, and send actions. It does not cover every operational concern such as rate limits or auth, but it is significantly more transparent than a bare schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely long, run-on, and repetitive, including two overlapping capability lists before the core invocation instructions. It contains useful details but is not appropriately sized or front-loaded, making it hard for an agent to quickly locate the essential call guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex agent gateway with no output schema, the description covers many behavioral flows such as async processing, decision cards, monitor cards, and email drafts. However, it omits key invocation modes and parameters including adapter, calls, trigger, commit_ask, and commit_grant, leaving the overall context only moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 48% across 21 parameters, and the description explains only a few high-level inputs such as intent, use_case, context, and request_id. It leaves important parameters like adapter, calls, trigger, session_id, commit_ask, commit_grant, and input_responses largely or entirely unexplained in the prose, so it does not compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the core purpose: process a user request via intent or use_case and return a finished result. It also enumerates the supported capabilities, but the actual invocation guidance is buried after a long, sprawling capability list, so the tool's role is clear but not crisply front-loaded.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit usage guidance: send the request as intent, use use_case instead to find an adapter, pass context when available, and use request_id for long-running calls. Since there are no sibling tools, it cannot provide alternatives, but it still clearly explains when to use different input modes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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