developer-toolkit-mcp
Server Details
The documentation, as a tool your agent can call: 950+ AI-dev guides. Search + fetch tools.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mjaskolski/developer-toolkit-mcp
- GitHub Stars
- 0
Available Tools
2 toolsfetchFetch a documentation articleARead-onlyInspect
Retrieve the complete markdown of one documentation article by the id returned from search (for example en/claude-code/advanced-techniques/hooks-automation).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Article id from a `search` result. |
Output Schema
| Name | Required | Description |
|---|---|---|
| id | Yes | |
| url | Yes | |
| text | Yes | |
| title | Yes | |
| metadata | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, covering the safety profile. The description adds that the output is markdown and the id source, but doesn't disclose additional behavioral traits such as pagination or error handling. Since annotations carry the main transparency load, the added value is modest.
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 directly states the action and the parameter source. Every word earns its place with no redundancy or 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?
The tool is simple with one parameter, read-only annotations, and an output schema. The description covers the essential workflow (use id from search), and the output schema handles return values, so no additional information is needed for completeness.
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%, and the schema already describes `id` as 'Article id from a `search` result.' The description repeats the same information without adding new meaning, so it doesn't compensate beyond the baseline for high schema coverage.
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 specifies the verb 'Retrieve' and the resource 'complete markdown of one documentation article', and it explicitly mentions the id comes from `search`, distinguishing it from the sibling tool. The purpose is unmistakable.
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 states that the id must come from a `search` result, which implies usage after search. It provides clear context on how to retrieve the id, but it doesn't explicitly mention when not to use this tool or name alternatives beyond the implied `search` workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchSearch the documentationARead-onlyInspect
Search the AI Developer Toolkit documentation: 950+ guides on Cursor, Claude Code and OpenAI Codex, covering setup, agent workflows, hooks, MCP, testing, CI and deployment, in English and Polish. Returns ranked results; pass a result id to fetch for the full text.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural-language query or keywords. Polish queries return Polish articles. |
Output Schema
| Name | Required | Description |
|---|---|---|
| results | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only and closed-world. The description adds extra context about returning ranked results and the bilingual (English/Polish) nature, which goes beyond the annotations. This is useful but not over-elaborated, so a 4 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?
The description is two sentences, front-loads the tool's purpose and scope, and wastes no words. It efficiently communicates all needed information without 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?
With a clear scope, ranked results, language coverage, and a pointer to the sibling tool for full text, combined with read-only annotations and an output schema, the description is complete. There is no missing behavioral or workflow context for this simple tool.
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 description already fully covers the `query` parameter (100% coverage), and the description does not add further parameter-specific meaning. The description mentions Polish and English, but that overlaps with schema information about Polish queries, so the added value is minimal.
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 identifies the tool as a search over the AI Developer Toolkit documentation, specifies the covered topics and languages, and distinguishes itself from the sibling tool `fetch` by stating that full text is retrieved via a result id.
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?
It explicitly states the workflow: 'pass a result id to fetch for the full text' – indicating when to use fetch and that search is for initial ranked results. This provides clear alternative usage for full text retrieval.
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.
2 tool updates
- First observed
fetch - First observed
search
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TDQS
The two tools have completely distinct purposes: search queries the documentation index, while fetch retrieves a specific article by ID. There is no overlap or ambiguity between them.
Both tool names are single lowercase verbs ('search', 'fetch'), which is consistent in style. However, they lack a noun prefix (e.g., 'search_docs', 'fetch_article'), but the pattern is uniform and predictable.
With only 2 tools, the set feels minimal but is perfectly scoped for a documentation search-and-retrieve utility. It's on the low end of acceptable, but the narrow purpose justifies the small count.
The search-fetch pair covers the core workflow for documentation lookup. A 'list' or 'browse' tool could be useful, but for a search-driven retrieval server, these two tools satisfy the primary use case without major gaps.