bitHuman docs
Server Details
The bitHuman docs over MCP: two read-only tools, search and fetch; it needs no account and no key.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- bithuman-product/public-docs
- GitHub Stars
- 0
TDQS
Scored across 2 tools
search and fetch have clearly distinct purposes: search discovers pages, fetch retrieves a specific page. There is no overlap, and the descriptions reinforce the intended workflow.
Both tools use a single, lowercase verb (search, fetch), which is a consistent and predictable naming pattern. No mixed conventions are present.
Two tools are sufficient for a documentation retrieval server, and each earns its place. However, the count is slightly below the typical 3–15 range, so it's not maximal.
The search and fetch pair covers the full lifecycle of finding and reading documentation pages. No obvious gaps exist for the stated purpose of accessing bitHuman docs.
Available Tools
2 toolsfetchFetch a bitHuman docs pageARead-onlyIdempotentInspect
Fetch one docs page as markdown by the id search returned (a path such as /platforms/python), or by its full docs.bithuman.ai URL.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | A page path (/platforms/python) or URL (https://docs.bithuman.ai/platforms/python). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds value by disclosing the return format ('as markdown'), which is not in the annotations or schema.
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 front-loaded sentence with the verb, resource, format and input contract, plus a concrete example path. No filler.
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 one-parameter, read-only, idempotent fetch with full schema coverage and complete annotations, the description covers the input contract and return format. No output schema is needed since the markdown return is stated.
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 the baseline is 3, but the description adds meaning beyond the schema by explaining that `id` is the value returned by the `search` tool, not an arbitrary string. That provenance is not captured in the schema's own description.
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 verb and resource ('Fetch one docs page as markdown') and names the sibling it complements by tying the input to `search` results. An agent can distinguish it from `search` without opening either schema.
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 phrase 'by the id `search` returned' explicitly establishes the prerequisite that `search` runs first, which is real routing guidance. It stops short of stating when not to use this tool or any error/fallback condition, so it is not a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchSearch the bitHuman docsARead-onlyIdempotentInspect
Search docs.bithuman.ai (bitHuman real-time avatar SDKs, the REST API, deployment options, models, pricing). Returns the best-matching pages, each with an id to pass to fetch.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many results (default 8). | |
| query | Yes | What to look for, e.g. "Android first frame" or "LiveKit secret". | |
| section | No | Limit to one section. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world corpus), so the bar is lower. The description adds genuinely useful behavioral context by disclosing the return shape — best-matching pages with an id for `fetch` — which matters because no output schema exists to document this.
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 tight sentences with zero padding. The scope of the corpus is front-loaded and the handoff to `fetch` is placed last, matching the order an agent needs the information.
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 three-parameter search tool with no output schema, the description supplies the two things an agent most needs: what corpus is searched and what the results look like. The only minor gap is guidance on result quality or what to do when no match is found, which is not strictly required.
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%, with each of the three parameters documented (query examples, limit default/max, section enum), so the baseline is 3. The description's list of covered topics loosely maps to the section enum but adds no syntax or format guidance beyond what the schema already provides.
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 verb and resource ('Search docs.bithuman.ai') and enumerates the covered corpus (avatar SDKs, REST API, deployment, models, pricing). It also distinguishes itself from its sibling by explaining that result ids are meant to be passed to `fetch`, so the retrieval-then-fetch pipeline 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 makes clear this is the entry point for documentation lookup and that its output feeds `fetch`, which implies when to use it. It does not state explicit exclusions (e.g., what to do if search returns nothing, or when to skip straight to fetch), so it falls short of a full when/when-not statement.
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.
2 tool updates
- First observed
fetch - First observed
search
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