Full-text search across entity names and predicates; returns the most recent matching evidence-backed facts incl. provenance. Use when the target organization or metric name is fuzzy.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only and idempotent behavior, and the description adds useful result semantics: only the most recent matches, evidence-backed, and including provenance. This goes beyond the structured hints 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?
Two sentences with no fluff: the action and return value are front-loaded, followed by the usage condition. Every phrase adds signal.
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 simple read-only search tool with one required parameter, the description communicates what it searches, what it returns, and when to use it. Without an output schema, the prose about provenance and recency is sufficient; only minor details like limit defaults are missing.
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 carries the burden. It implies that 'query' is a fuzzy full-text string over entity names and predicates, but it never mentions the 'limit' parameter or its default behavior, leaving a visible gap.
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: full-text search across entity names and predicates returning evidence-backed facts with provenance. The fuzzy-target use case distinguishes it from siblings like get_facts and lookup_entity.
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?
Explicitly says to use this when the target organization or metric name is fuzzy, which gives the agent a clear selection condition. It does not name alternatives or exclusion cases, so it stops short of full when-not guidance.
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.
get_facts, query_template, and search_facts all return fact-like results and can overlap when an agent needs a specific reported value; the descriptions attempt to differentiate curated vs. full-text paths, but the boundary is not crisp. lookup_entity, list_templates, and mcp_server_history are clearly distinct.
Most tools follow a verb_noun pattern: get_facts, list_templates, lookup_entity, query_template, search_facts. mcp_server_history breaks the pattern by using a bare noun phrase, which is inconsistent with the rest of the set.
Six tools is a well-scoped size for a fact-registry MCP server. The count is neither bloated nor too thin, though mcp_server_history feels somewhat unrelated to the core fact-querying purpose.
The server covers the main read-side needs of the domain: entity resolution, full-text search, direct fact retrieval, and template-based structured queries. Minor gaps exist, such as no tool to fetch a single fact by fact_url or inspect historical changes to a fact, but core workflows are supported.