rfcFetch IETF Datatracker metadata for an RFC by number (e.g. 9000); returns title, status, authors, publication date, and abstract.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| results | No | Array of matching documents |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds useful behavioral context by specifying the source (Datatracker) and the exact returned fields (title, status, authors, publication date, abstract), which goes beyond the annotations without contradicting 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, front-loaded sentence that includes the action, resource, example, and return fields. It is compact and free of unnecessary 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 (one parameter) and has an output schema, so the description does not need to explain return structure. It covers purpose, parameter meaning, and typical returns, making it complete for effective 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 coverage is 0%, with only a 'number' property and no description. The description fully compensates by clarifying the parameter is an 'RFC number' and giving examples (9000, 2616), making the semantics immediately clear.
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 'Fetch IETF Datatracker metadata for an RFC by number' with a specific verb and resource, plus an example (9000). It distinguishes from siblings like 'wg' and 'wgs_search' by focusing specifically on RFC metadata rather than working groups.
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 usage when you have an RFC number ('by number'), but it does not explicitly mention alternatives or when not to use it. This is clear context without exclusions, fitting the 'clear context, no exclusions' level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have overlapping or poorly distinguished purposes. For instance, `ask_pipeworx` and `ask_pipeworx_beta` have nearly identical descriptions, and `ask_pipeworx_grounded` also shares the same routing but adds a different output format. The `ai_visibility_check` and `scan_competitor_ai_presence` tools also overlap significantly.
There is some consistency with verb_noun patterns (e.g., `resolve_entity`, `search_within`, `subscribe`, `unsubscribe`). However, there are many deviations: `ask_pipeworx`, `pipeworx_feedback`, `pipeworx_trending`, `entity_profile`, `scan_dependency`, and `polymarket_edges` break the pattern, mixing descriptive names with non-standard prefixes.
37 tools is slightly above the ideal range for a single MCP server, but the tools cover a very broad and varied domain (IETF data, company research, prediction markets, package scanning, memory, etc.). The count is high but still within a manageable scope for a multi-purpose utility server.
The server combines tools from two very different domains: IETF Datatracker (document/WG/person lookups) and Pipeworx (data retrieval, prediction markets, company analysis). The IETF-related tools are sparse and incomplete (only document search, document, person, wg, wgs_search, rfc are present—no ability to create or modify records). The Pipeworx side is extensive but leaves notable gaps (e.g., no tool for submitting comments or editing IETF documents).