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HelpCode-ai

anythingmcp

by HelpCode-ai
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TypeScript
Remote

Server Quality Checklist

83%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.4.2

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: overview introduces the product, get_started guides installation, connect_client explains client integration, and list_connectors catalogs integrations. No overlap or ambiguity.

    Naming Consistency5/5

    All tools follow a consistent 'anythingmcp_verb_noun' pattern (connect_client, get_started, list_connectors, overview). The naming is uniform and predictable.

    Tool Count5/5

    With 4 tools, the set is tightly scoped to the server's purpose of onboarding and exploring AnythingMCP. Each tool earns its place, and the count is appropriate for the domain.

    Completeness4/5

    The tools cover the core user journey: overview, installation, client connection, and integration discovery. Minor gaps exist (e.g., no tool for advanced configuration or troubleshooting), but the essential needs are met.

  • Average 4.6/5 across 4 of 4 tools scored.

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

    • 4 of 5 community issues answered or closed in the last 6 months
    • 251 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under AGPL 3.0.

  • 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.

  • This repository includes a glama.json configuration file.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • View related servers

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

  • Behavior4/5

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

    Annotations already provide readOnlyHint and idempotentHint, and the description reinforces 'Read-only, no side effects.' It adds value by specifying the output type ('plain-text setup instructions'), but does not elaborate further on behaviors like rate limits or auth.

    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?

    Two sentences, minimal waste, front-loaded with key info (read-only, no side effects, plain-text instructions). Every sentence adds value.

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

    Completeness5/5

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

    For a simple read-only tool with one enum parameter, the description covers purpose, usage context, and output format. No output schema is needed as the result is plain text. Complete for its complexity.

    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?

    Schema coverage is 100% with enum and description for the sole parameter. The description adds no additional semantics beyond what the schema already provides, meeting the baseline for high coverage.

    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?

    Clearly states the tool returns 'plain-text setup instructions for connecting ONE AI client to an AnythingMCP server; pass the required `client`.' This is specific, uses a verb+resource structure, and differentiates from siblings like anythingmcp_get_started.

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

    Usage Guidelines5/5

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

    Explicitly tells when to use: 'Use this once you already have an AnythingMCP instance running; to install one first, use anythingmcp_get_started.' This provides clear context and an alternative.

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

  • Behavior4/5

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

    The description adds value beyond annotations by detailing the output format (plain-text catalog), specific contents (categories, connector types, link), and reinforces the read-only nature. With annotations already providing readOnlyHint and idempotentHint, the description enriches behavioral understanding.

    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 three sentences, front-loaded with key behavioral info, and every sentence provides useful information without redundancy. It is efficiently structured.

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

    Completeness5/5

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

    For a parameterless tool with no output schema, the description covers the return value (plain-text catalog with categories and link) comprehensively. It is complete for the tool's purpose of discovery.

    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 input schema has no parameters (100% coverage, 0 params). The description doesn't need to add parameter information since there are none. Baseline for 0 parameters is 4.

    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 'Returns a plain-text catalog of AnythingMCP's 175+ pre-built connectors grouped by category... plus the 5 connector types you can build with no code'. It identifies the specific verb and resource, and the content clearly distinguishes this from sibling tools like 'connect_client' or 'get_started'.

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

    Usage Guidelines4/5

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

    The tool explicitly says 'Use this to discover available integrations before connecting a client', providing clear context for when to use it. While it doesn't explicitly state when not to use it or mention alternatives, the guidance is sufficient for an agent.

    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?

    Annotations already declare readOnlyHint=true and idempotentHint=true. The description redundantly states 'Read-only, no side effects,' which adds no new behavioral context beyond what annotations already provide.

    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?

    Single sentence with clear front-loading: 'Read-only, no side effects. Returns a concise plain-text overview...' No wasted words.

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

    Completeness5/5

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

    Complete for a parameterless, read-only tool with good annotations. Description covers what it does, why to call it, and how to proceed with sibling tools.

    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 in schema, so baseline is 4. Description does not need to add parameter info and doesn't.

    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?

    Description explicitly states the tool returns a concise plain-text overview of AnythingMCP with links, and distinguishes it from siblings by specifying it should be called first to understand the product.

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

    Usage Guidelines5/5

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

    Explicitly says 'Call this FIRST' and then lists when to use three specific sibling tools (anythingmcp_get_started, anythingmcp_connect_client, anythingmcp_list_connectors), providing clear guidance on tool selection.

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

  • Behavior5/5

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

    Description starts with 'Read-only, no side effects', confirming annotations. Adds context about returning plain-text steps.

    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?

    Two sentences, front-loaded with key behaviors, no wasted words.

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

    Completeness5/5

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

    Given no parameters and no output schema, the description is complete, covering purpose, side effects, and use case differentiation.

    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; baseline 4. Description doesn't need to add parameter info.

    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?

    Clear verb+resource: returns copy-pasteable steps to install/run AnythingMCP. Distinguishes from sibling 'anythingmcp_connect_client'.

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

    Usage Guidelines5/5

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

    Explicitly states when to use (deploy AnythingMCP) and when not (for connecting, use alternative). Provides clear context.

    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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