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Anam MCP Server

Anam MCP Server

Official
by anam-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

search_knowledge_group

Search a knowledge group for relevant documents using a query. Provide a group ID and search terms to retrieve matching results.

Instructions

Search within a knowledge group for relevant documents.

Args: group_id: The UUID of the knowledge group to search query: Search query limit: Maximum number of results

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "group_id": "<group_id>",
      "query": "<query>"
    },
    "name": "search_knowledge_group"
  }
}

Input Schema

NameRequiredDescriptionDefault
group_idYes
queryYes
limitNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.13

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavior. It only states the basic operation without details on whether the search is read-only, what aspects are searched (title, content, metadata), required permissions, or result ranking. The presence of an output schema is not referenced, leaving return value behavior unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loads the main purpose. However, the Args section repeats parameter types already in the schema; it could be omitted or integrated more concisely. Overall, it is efficient but not perfectly lean.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the existence of an output schema, the description still lacks details on return values and search behavior (e.g., whether results are ranked, pagination). With no annotations and many sibling tools, more context (e.g., when to use search vs list) is needed for completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. The Args section adds basic parameter explanations, but they are minimal—e.g., query format and limit default behavior are not elaborated. For a search tool with only 3 parameters, this offers little beyond what an annotated schema would provide.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action 'Search' and the resource 'within a knowledge group for relevant documents.' It distinguishes itself from sibling search tools (e.g., search_avatars, search_voices) by specifying the knowledge group context, and from list_knowledge_documents by implying a query-based search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. For example, it does not mention that list_knowledge_documents should be used to retrieve all documents without a query, or that search_avatars is for avatar searches. The description assumes the agent knows the context without explicit direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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