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fastmcp-me

Apache Doris MCP Server

by fastmcp-me
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Python
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.1

  • Disambiguation5/5

    Each tool has a distinct purpose: executing SELECT queries, listing databases, and listing tables. No overlap in functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (execute_query, show_databases, show_tables), making them predictable.

    Tool Count3/5

    Three tools is on the low side for a database server, but it's acceptable for a minimal read-only interface. The scope feels thin but not extreme.

    Completeness2/5

    The tool set lacks write operations (INSERT, UPDATE, DELETE), DDL commands (CREATE, DROP, ALTER), and metadata queries (DESCRIBE). Significant gaps for a database server.

  • Average 3.7/5 across 3 of 3 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

  • This repository is licensed under Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior3/5

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

    The description mentions 'timeout protection,' which is a behavioral trait beyond the schema. However, it lacks details on error handling, idempotency, rate limits, or whether the tool is read-only. Since no annotations are provided, the description carries the full burden but remains brief.

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

    Conciseness5/5

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

    The description is extremely concise with a single opening line, structured Args and Returns sections, and zero wasted words. It is easy to scan and front-loaded with the key action.

    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 tool's simplicity (one parameter, no output schema), the description covers the basic function but omits details like whether modifications are allowed, timeout behavior, and exact return format beyond 'List[Dict]'. Adequate but could be more complete.

    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?

    With schema description coverage at 0%, the description must compensate. It describes the single 'query' parameter as 'The SQL query to execute,' which adds minimal meaning beyond the parameter name. It could clarify expected format (e.g., SELECT only) but is adequate.

    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 tool runs SELECT queries against Doris with timeout protection, using specific verb and resource. It distinguishes from sibling tools (show_databases, show_tables) which are for listing databases/tables rather than executing queries.

    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 like show_databases/show_tables. There is no mention of prerequisites, constraints (e.g., only SELECT queries), or when to avoid using it.

    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?

    With no annotations, the description should disclose behavioral traits. It notes the return type (List[str]) but omits whether the operation is read-only, safe, or requires any permissions. Basic info only.

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

    Conciseness5/5

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

    Extremely concise: two sentences with clear purpose and return type. No wasted words.

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

    Completeness4/5

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

    For a zero-parameter tool that lists databases, the description covers purpose and return type adequately. Missing details like ordering or potential errors, but overall complete for simple use.

    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?

    No parameters exist, and schema coverage is 100%. Baseline for 0 parameters is 4, and the description adds value by specifying the return type. No additional param info needed.

    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 verb 'List' and resource 'all databases', distinguishing it from sibling tools 'show_tables' (tables) and 'execute_query' (arbitrary queries).

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

    Usage Guidelines3/5

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

    The usage is implied: when you need a list of databases. However, no explicit guidance on when not to use (e.g., if you need detailed info) or alternatives like 'execute_query' for custom listings.

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

  • Behavior3/5

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

    No annotations are provided, so the description carries full burden. It explains the return format as a list of dictionaries, but lacks details on potential side effects (none expected for a listing operation) or authorization needs. This is adequate for a simple read tool.

    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 well-structured with Args and Returns sections. It is concise but includes all necessary parts. Minor improvement could be dropping the Returns section if redundant, but it adds clarity.

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

    Completeness4/5

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

    Given no output schema and no annotations, the description covers the essential: purpose, parameter semantics, and return format. It lacks details on filter syntax and result ordering, but for a simple listing tool, it is mostly complete.

    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?

    Schema coverage is 0%, meaning the schema has no descriptions. The description adds meaning by specifying 'database: The database name' and 'like: Optional pattern to filter table names,' which goes beyond the schema's bare type and title. However, it does not specify the pattern format (e.g., SQL LIKE syntax).

    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 'List all tables in the specified database,' which is a specific verb and resource. It naturally distinguishes from sibling tools like show_databases (which lists databases) and execute_query (which runs SQL).

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

    Usage Guidelines3/5

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

    The description implies usage for listing tables but does not explicitly provide when-to-use or when-not-to-use guidance. However, given the distinct sibling tools, confusion is unlikely.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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