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lesskao

SNOMED GraphRAG MCP Server

by lesskao
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Remote

Server Quality Checklist

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Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: graph_search_concept retrieves concepts by search, and graph_get_related fetches related concepts via relationships. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tools follow the consistent 'graph_<verb>_<noun>' pattern with snake_case. 'graph_search_concept' and 'graph_get_related' are parallel and predictable.

    Tool Count2/5

    With only 2 tools for a complex domain like SNOMED CT, the server is severely under-scoped. Typical SNOMED interactions require many more operations (e.g., detail retrieval, hierarchy browsing, multiple relation types).

    Completeness2/5

    The tool surface has major gaps: no tool to get full concept details (descriptions, synonyms), no hierarchy navigation, and graph_get_related is limited to a single relation type (SPECIMEN_SOURCE_IDENTITY). Missing core CRUD-like operations for a knowledge graph.

  • Average 3.1/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    No annotations are provided, so the description bears full responsibility for behavioral disclosure. It merely states '获取' (fetch), implying a read operation, but does not explicitly declare read-only behavior, auth requirements, rate limits, or any side effects. This is insufficient for an agent to assess safety.

    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 extremely concise, consisting of one purpose sentence and two parameter clarifications. No words are wasted. The structure is front-loaded with the main action. The only drawback is the slightly awkward grammar in the first sentence, but it remains efficient.

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

    Completeness3/5

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

    Given the low complexity (2 parameters) and presence of an output schema (not shown), the description does not need to detail return values. However, it fails to mention whether any side effects occur or what the output represents. The behavioral gap leaves the agent with incomplete context for safe invocation. It is adequate but not thorough.

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

    Parameters3/5

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

    Input schema description coverage is 0%, making the description critical. It explains 'sctid' as '概念 sctid' and 'rel_types' as '关系类型列表，默认 [SPECIMEN_SOURCE_IDENTITY]', adding context beyond the bare schema fields. However, it does not enumerate allowed values for 'rel_types' or explain the default behavior fully. The added value is moderate but not comprehensive.

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

    Purpose3/5

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

    The description states the tool '获取概念的通过 RoleGroup 的定义关系及目标概念', which indicates fetching definition relations and target concepts via RoleGroup. However, the phrasing is somewhat ambiguous and does not distinguish from the sibling tool 'graph_search_concept', leaving the agent unclear about when to use this vs. 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. The description does not explain prerequisites, typical scenarios, or exclusions. The agent receives no help in deciding between this tool and 'graph_search_concept'.

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

  • Behavior2/5

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

    No annotations are present, so the description must fully disclose behavioral traits. It only mentions search criteria and parameters but omits key details such as behavior on no results, pagination, performance characteristics, or error handling. The existence of an output schema is not leveraged in the description.

    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 very short (two lines) and includes parameter explanations, avoiding unnecessary fluff. However, it could be slightly more structured (e.g., separating purpose from parameter details) without losing conciseness.

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

    Completeness3/5

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

    Given that an output schema exists and parameters are few, the description is minimally adequate for a basic search tool. It covers the core functionality but lacks edge-case handling, error states, or performance notes that would make it fully complete for an agent unfamiliar with SNOMED.

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

    Parameters4/5

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

    The description adds meaning beyond the schema by explaining that 'keyword' is an FSN substring or sctid, and 'limit' is the number of returned results. Since schema description coverage is 0%, this compensation is valuable, though it could specify the default limit explicitly.

    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 explicitly states the tool searches for concepts in the SNOMED graph using FSN or sctid. It clearly identifies the verb ('检索' - retrieve/search) and resource ('概念' - concepts), and differentiates from the sibling tool graph_get_related by specifying the search method.

    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 guidelines are provided about when to use this tool versus alternatives. The sibling graph_get_related is listed but the description does not mention any context, prerequisites, or exclusion criteria, leaving the agent without guidance for choosing the appropriate tool.

    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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