Skip to main content
Glama
renCosta2025

Context7 MCP

by renCosta2025
OverviewSchemaRelated ServersScoreDiscussions
Hybrid

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct and non-overlapping purposes: 'resolve-library-id' handles name resolution to obtain a compatible library ID, while 'get-library-docs' fetches documentation using that ID. Their descriptions explicitly define their roles and interdependency, leaving no ambiguity about when to use each tool.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with kebab-case formatting ('resolve-library-id' and 'get-library-docs'), using clear action verbs ('resolve' and 'get') paired with descriptive nouns. This consistency makes the tool set predictable and easy to understand.

    Tool Count2/5

    With only 2 tools, the server feels under-scoped for its apparent domain of library documentation retrieval. While the tools cover core resolution and fetching, typical documentation systems might include additional operations like searching, listing libraries, or managing documentation versions, making this set feel incomplete for robust agent workflows.

    Completeness2/5

    The tool set is severely incomplete for a documentation server, lacking essential operations such as searching for libraries, listing available libraries, or handling documentation updates. It forces a rigid two-step process without alternatives, creating potential dead ends if users need broader exploration or management capabilities.

  • Average 4.2/5 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 is passing

  • This repository is licensed under MIT License.

  • 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.

  • Add a glama.json file to provide metadata about your server.

  • 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.

  • Add related servers to improve discoverability.

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?

    With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool 'fetches up-to-date documentation' which implies read-only behavior, but doesn't explicitly state whether this requires authentication, has rate limits, or what format the documentation returns. It adds some context about the ID requirement but lacks comprehensive behavioral details.

    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 efficiently structured in two sentences that each serve distinct purposes: the first states the core function, the second provides critical usage guidance. There's no wasted language, and the most important information (the prerequisite requirement) is appropriately front-loaded in the second sentence.

    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?

    For a tool with 3 parameters, 100% schema coverage, and no output schema, the description provides adequate but not comprehensive context. It explains the prerequisite relationship with the sibling tool well, but doesn't address what the documentation output looks like or any behavioral constraints beyond the ID requirement. The absence of annotations means more behavioral context would be helpful.

    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 description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds minimal value beyond the schema - it mentions the library ID requirement and format but doesn't provide additional semantic context about the parameters beyond what's already in the schema descriptions.

    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 ('fetches up-to-date documentation') and resource ('for a library'), making the purpose specific and unambiguous. It distinguishes from the sibling 'resolve-library-id' by explaining this tool retrieves documentation while the sibling resolves IDs, establishing clear functional separation.

    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?

    The description provides explicit guidance on when to use this tool versus alternatives: it instructs to call 'resolve-library-id' first unless the user provides a library ID in specific formats. This creates clear prerequisites and decision rules for the agent, directly addressing the sibling relationship.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the selection process (prioritization criteria like name similarity, description relevance, documentation coverage, trust score), response format expectations, and handling of edge cases (ambiguous queries, no matches). However, it doesn't mention potential limitations like rate limits or authentication requirements.

    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 clear sections (usage rule, selection process, response format) and avoids redundancy. However, it includes some implementation details (e.g., 'analyze the query') that might be more appropriate for agent instructions rather than tool description, slightly reducing efficiency.

    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 the tool's complexity (involving matching algorithms and multiple output scenarios) and lack of output schema, the description does a good job explaining the expected response format and edge cases. However, it could benefit from more detail on the return structure (e.g., data types) to fully compensate for the missing output schema.

    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 description coverage is 100% for the single parameter 'libraryName', so the schema already documents it adequately. The description doesn't add significant semantic context beyond what the schema provides (e.g., examples of valid library names or formatting nuances), resulting in a baseline score of 3.

    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 specific verb 'resolves' and resource 'package/product name to a Context7-compatible library ID', and explicitly distinguishes it from its sibling 'get-library-docs' by stating it must be called first unless the user provides a library ID. This provides excellent differentiation and clarity.

    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?

    The description provides explicit guidance on when to use this tool ('before get-library-docs') and when not to use it ('unless the user explicitly provides a library ID'). It names the alternative scenario and sibling tool, offering comprehensive usage instructions.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

context7fork MCP server

Copy to your README.md:

Score Badge

context7fork MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/renCosta2025/context7fork'

If you have feedback or need assistance with the MCP directory API, please join our Discord server