Claim history of a REMOTE MCP server from FACTANKER's own periodic probes (initialize + tools/list every 6h): availability, tool count and contract changes over time, each with evidence. Use when asked whether an MCP endpoint exists, is stable, or changed its tools.
| Name | Required | Description | Default |
|---|---|---|---|
| since | No | ISO-Datum: nur Aenderungen ab diesem Tag | |
| endpoint | Yes | Endpunkt-URL oder Registry-Name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and idempotentHint annotations, the description discloses that data comes from periodic probes every 6 hours, that it tracks initialize + tools/list results, and that changes are accompanied by evidence. This helps an agent understand the data's freshness and what kind of history is available.
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 dense sentence that packs the source, cadence, tracked metrics, and usage trigger with no filler. The core scope—'REMOTE MCP server' and 'periodic probes'—is front-loaded.
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 read-only tool with two simple parameters, the description covers source, cadence, recorded fields, evidence, and use cases. It does not describe the exact response shape, but given the absence of an output schema and the straightforward nature of the result, this is a minor gap.
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%, so the endpoint and since parameters are already explained in the input schema. The tool description adds useful context about what the history captures but does not need to restate parameter meanings.
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?
Describes the tool as 'Claim history of a REMOTE MCP server from FACTANKER's own periodic probes' and names concrete outputs: 'availability, tool count and contract changes over time, each with evidence.' This clearly distinguishes it from the sibling fact/template/query tools, which address different resources.
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 gives an explicit trigger: 'Use when asked whether an MCP endpoint exists, is stable, or changed its tools.' It does not explicitly name alternatives or state when not to use it, but the intended use cases are clear and sufficiently scoped.
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.