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❌ Without Context7

LLMs rely on outdated or generic information about the libraries you use. You get:

  • ❌ Code examples are outdated and based on year-old training data

  • ❌ Hallucinated APIs don't even exist

  • ❌ Generic answers for old package versions

Related MCP server: Context7 MCP

✅ With Context7

Context7 MCP pulls up-to-date, version-specific documentation and code examples straight from the source — and places them directly into your prompt.

Add use context7 to your prompt in Cursor:

Create a Next.js middleware that checks for a valid JWT in cookies and redirects unauthenticated users to `/login`. use context7
Configure a Cloudflare Worker script to cache JSON API responses for five minutes. use context7

Context7 fetches up-to-date code examples and documentation right into your LLM's context.

  • 1️⃣ Write your prompt naturally

  • 2️⃣ Tell the LLM to use context7

  • 3️⃣ Get working code answers

No tab-switching, no hallucinated APIs that don't exist, no outdated code generations.

📚 Adding Projects

Check out our project addition guide to learn how to add (or update) your favorite libraries to Context7.

🛠️ Installation

Requirements

  • Node.js >= v18.0.0

  • Cursor, Windsurf, Claude Desktop or another MCP Client

To install Context7 MCP Server for any client automatically via Smithery:

npx -y @smithery/cli@latest install @upstash/context7-mcp --client <CLIENT_NAME> --key <YOUR_SMITHERY_KEY>

You can find your Smithery key in the Smithery.ai webpage.

Go to: Settings -> Cursor Settings -> MCP -> Add new global MCP server

Pasting the following configuration into your Cursor ~/.cursor/mcp.json file is the recommended approach. You may also install in a specific project by creating .cursor/mcp.json in your project folder. See Cursor MCP docs for more info.

Since Cursor 1.0, you can click the install button below for instant one-click installation.

Cursor Remote Server Connection

Install MCP Server

{
  "mcpServers": {
    "context7": {
      "url": "https://mcp.context7.com/mcp"
    }
  }
}

Cursor Local Server Connection

Install MCP Server

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

Install MCP Server

{
  "mcpServers": {
    "context7": {
      "command": "bunx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

Install MCP Server

{
  "mcpServers": {
    "context7": {
      "command": "deno",
      "args": ["run", "--allow-env=NO_DEPRECATION,TRACE_DEPRECATION", "--allow-net", "npm:@upstash/context7-mcp"]
    }
  }
}

Add this to your Windsurf MCP config file. See Windsurf MCP docs for more info.

Windsurf Remote Server Connection

{
  "mcpServers": {
    "context7": {
      "serverUrl": "https://mcp.context7.com/sse"
    }
  }
}

Windsurf Local Server Connection

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

Use the Add manually feature and fill in the JSON configuration information for that MCP server. For more details, visit the Trae documentation.

Trae Remote Server Connection

{
  "mcpServers": {
    "context7": {
      "url": "https://mcp.context7.com/mcp"
    }
  }
}

Trae Local Server Connection

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": [
        "-y",
        "@upstash/context7-mcp"
      ]
    }
  }
}

Add this to your VS Code MCP config file. See VS Code MCP docs for more info.

VS Code Remote Server Connection

"mcp": {
  "servers": {
    "context7": {
      "type": "http",
      "url": "https://mcp.context7.com/mcp"
    }
  }
}

VS Code Local Server Connection

"mcp": {
  "servers": {
    "context7": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

You can configure Context7 MCP in Visual Studio 2022 by following the Visual Studio MCP Servers documentation.

Add this to your Visual Studio MCP config file (see the Visual Studio docs for details):

{
  "mcp": {
    "servers": {
      "context7": {
        "type": "http",
        "url": "https://mcp.context7.com/mcp"
      }
    }
  }
}

Or, for a local server:

{
  "mcp": {
    "servers": {
      "context7": {
        "type": "stdio",
        "command": "npx",
        "args": ["-y", "@upstash/context7-mcp"]
      }
    }
  }
}

For more information and troubleshooting, refer to the Visual Studio MCP Servers documentation.

It can be installed via Zed Extensions or you can add this to your Zed settings.json. See Zed Context Server docs for more info.

{
  "context_servers": {
    "Context7": {
      "command": {
        "path": "npx",
        "args": ["-y", "@upstash/context7-mcp"]
      },
      "settings": {}
    }
  }
}

See Gemini CLI Configuration for details.

  1. Open the Gemini CLI settings file. The location is ~/.gemini/settings.json (where ~ is your home directory).

  2. Add the following to the mcpServers object in your settings.json file:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

If the mcpServers object does not exist, create it.

Run this command. See Claude Code MCP docs for more info.

Claude Code Remote Server Connection

claude mcp add --transport http context7 https://mcp.context7.com/mcp

Or using SSE transport:

claude mcp add --transport sse context7 https://mcp.context7.com/sse

Claude Code Local Server Connection

claude mcp add context7 -- npx -y @upstash/context7-mcp

Add this to your Claude Desktop claude_desktop_config.json file. See Claude Desktop MCP docs for more info.

{
  "mcpServers": {
    "Context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

You can easily install Context7 through the Cline MCP Server Marketplace by following these instructions:

  1. Open Cline.

  2. Click the hamburger menu icon (☰) to enter the MCP Servers section.

  3. Use the search bar within the Marketplace tab to find Context7.

  4. Click the Install button.

Open the "Settings" page of the app, navigate to "Plugins," and enter the following JSON:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

Once saved, enter in the chat get-library-docs followed by your Context7 documentation ID (e.g., get-library-docs /nuxt/ui). More information is available on BoltAI's Documentation site. For BoltAI on iOS, see this guide.

If you prefer to run the MCP server in a Docker container:

  1. Build the Docker Image:

    First, create a Dockerfile in the project root (or anywhere you prefer):

    FROM node:18-alpine
    
    WORKDIR /app
    
    # Install the latest version globally
    RUN npm install -g @upstash/context7-mcp
    
    # Expose default port if needed (optional, depends on MCP client interaction)
    # EXPOSE 3000
    
    # Default command to run the server
    CMD ["context7-mcp"]

    Then, build the image using a tag (e.g., context7-mcp). Make sure Docker Desktop (or the Docker daemon) is running. Run the following command in the same directory where you saved the Dockerfile:

    docker build -t context7-mcp .
  2. Configure Your MCP Client:

    Update your MCP client's configuration to use the Docker command.

    Example for a cline_mcp_settings.json:

    {
      "mcpServers": {
        "Сontext7": {
          "autoApprove": [],
          "disabled": false,
          "timeout": 60,
          "command": "docker",
          "args": ["run", "-i", "--rm", "context7-mcp"],
          "transportType": "stdio"
        }
      }
    }

    Note: This is an example configuration. Please refer to the specific examples for your MCP client (like Cursor, VS Code, etc.) earlier in this README to adapt the structure (e.g., mcpServers vs servers). Also, ensure the image name in args matches the tag used during the docker build command.

The configuration on Windows is slightly different compared to Linux or macOS (Cline is used in the example). The same principle applies to other editors; refer to the configuration of command and args.

{
  "mcpServers": {
    "github.com/upstash/context7-mcp": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "@upstash/context7-mcp@latest"],
      "disabled": false,
      "autoApprove": []
    }
  }
}

To configure Context7 MCP in Augment Code, you can use either the graphical interface or manual configuration.

A. Using the Augment Code UI

  1. Click the hamburger menu.

  2. Select Settings.

  3. Navigate to the Tools section.

  4. Click the + Add MCP button.

  5. Enter the following command:

    npx -y @upstash/context7-mcp@latest
  6. Name the MCP: Context7.

  7. Click the Add button.

Once the MCP server is added, you can start using Context7's up-to-date code documentation features directly within Augment Code.


B. Manual Configuration

  1. Press Cmd/Ctrl Shift P or go to the hamburger menu in the Augment panel

  2. Select Edit Settings

  3. Under Advanced, click Edit in settings.json

  4. Add the server configuration to the mcpServers array in the augment.advanced object

"augment.advanced": { "mcpServers": [ { "name": "context7", "command": "npx", "args": ["-y", "@upstash/context7-mcp"] } ] }

Once the MCP server is added, restart your editor. If you receive any errors, check the syntax to make sure closing brackets or commas are not missing.

Add this to your Roo Code MCP configuration file. See Roo Code MCP docs for more info.

Roo Code Remote Server Connection

{
  "mcpServers": {
    "context7": {
      "type": "streamable-http",
      "url": "https://mcp.context7.com/mcp"
    }
  }
}

Roo Code Local Server Connection

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

To configure Context7 MCP in Zencoder, follow these steps:

  1. Go to the Zencoder menu (...)

  2. From the dropdown menu, select Agent tools

  3. Click on the Add custom MCP

  4. Add the name and server configuration from below, and make sure to hit the Install button

{
    "command": "npx",
    "args": [
        "-y",
        "@upstash/context7-mcp@latest"
    ]
}

Once the MCP server is added, you can easily continue using it.

Add this to your Amazon Q Developer CLI configuration file. See Amazon Q Developer CLI docs for more details.

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

See Qodo Gen docs for more details.

  1. Open Qodo Gen chat panel in VSCode or IntelliJ.

  2. Click Connect more tools.

  3. Click + Add new MCP.

  4. Add the following configuration:

{
  "mcpServers": {
    "context7": {
      "url": "https://mcp.context7.com/mcp"
    }
  }
}

See JetBrains AI Assistant Documentation for more details.

  1. In JetBrains IDEs go to Settings -> Tools -> AI Assistant -> Model Context Protocol (MCP)

  2. Click + Add.

  3. Click on Command in the top-left corner of the dialog and select the As JSON option from the list

  4. Add this configuration and click OK

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}
  1. Click Apply to save changes.

See Warp Model Context Protocol Documentation for details.

  1. Navigate Settings > AI > Manage MCP servers.

  2. Add a new MCP server by clicking the + Add button.

  3. Paste the configuration given below:

{
  "Context7": {
    "command": "npx",
    "args": [
      "-y",
      "@upstash/context7-mcp"
    ],
    "env": {},
    "working_directory": null,
    "start_on_launch": true
  }
}
  1. Click Save to apply the changes.

Add this to your Opencode configuration file. See Opencode MCP docs docs for more info.

Opencode Remote Server Connection

"mcp": {
  "context7": {
    "type": "remote",
    "url": "https://mcp.context7.com/mcp",
    "enabled": true
  }
}

Opencode Local Server Connection


{
  "mcp": {
    "context7": {
      "type": "local",
      "command": ["npx", "-y", "@upstash/context7-mcp"],
      "enabled": true
    }
  }
}

🔨 Available Tools

Context7 MCP provides the following tools that LLMs can use:

  • resolve-library-id: Resolves a general library name into a Context7-compatible library ID.

    • libraryName (required): The name of the library to search for

  • get-library-docs: Fetches documentation for a library using a Context7-compatible library ID.

    • context7CompatibleLibraryID (required): Exact Context7-compatible library ID (e.g., /mongodb/docs, /vercel/next.js)

    • topic (optional): Focus the docs on a specific topic (e.g., "routing", "hooks")

    • tokens (optional, default 10000): Max number of tokens to return. Values less than the default value of 10000 are automatically increased to 10000.

🛟 Tips

Add a Rule

If you don’t want to add use context7 to every prompt, you can define a simple rule in your .windsurfrules file in Windsurf or from Cursor Settings > Rules section in Cursor (or the equivalent in your MCP client) to auto-invoke Context7 on any code question:

[[calls]]
match = "when the user requests code examples, setup or configuration steps, or library/API documentation"
tool  = "context7"

From then on you’ll get Context7’s docs in any related conversation without typing anything extra. You can add your use cases to the match part.

Use Library Id

If you already know exactly which library you want to use, add its Context7 ID to your prompt. That way, Context7 MCP server can skip the library-matching step and directly continue with retrieving docs.

implement basic authentication with supabase. use library /supabase/supabase for api and docs

The slash syntax tells the MCP tool exactly which library to load docs for.

💻 Development

Clone the project and install dependencies:

bun i

Build:

bun run build

Run the server:

bun run dist/index.js

CLI Arguments

context7-mcp accepts the following CLI flags:

  • --transport <stdio|http|sse> – Transport to use (stdio by default).

  • --port <number> – Port to listen on when using http or sse transport (default 3000).

Example with http transport and port 8080:

bun run dist/index.js --transport http --port 8080
{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["tsx", "/path/to/folder/context7-mcp/src/index.ts"]
    }
  }
}
npx -y @modelcontextprotocol/inspector npx @upstash/context7-mcp

🚨 Troubleshooting

If you encounter ERR_MODULE_NOT_FOUND, try using bunx instead of npx:

{
  "mcpServers": {
    "context7": {
      "command": "bunx",
      "args": ["-y", "@upstash/context7-mcp"]
    }
  }
}

This often resolves module resolution issues in environments where npx doesn't properly install or resolve packages.

For errors like Error: Cannot find module 'uriTemplate.js', try the --experimental-vm-modules flag:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "--node-options=--experimental-vm-modules", "@upstash/context7-mcp@1.0.6"]
    }
  }
}

Use the --experimental-fetch flag to bypass TLS-related problems:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "--node-options=--experimental-fetch", "@upstash/context7-mcp"]
    }
  }
}
  1. Try adding @latest to the package name

  2. Use bunx as an alternative to npx

  3. Consider using deno as another alternative

  4. Ensure you're using Node.js v18 or higher for native fetch support

⚠️ Disclaimer

Context7 projects are community-contributed and while we strive to maintain high quality, we cannot guarantee the accuracy, completeness, or security of all library documentation. Projects listed in Context7 are developed and maintained by their respective owners, not by Context7. If you encounter any suspicious, inappropriate, or potentially harmful content, please use the "Report" button on the project page to notify us immediately. We take all reports seriously and will review flagged content promptly to maintain the integrity and safety of our platform. By using Context7, you acknowledge that you do so at your own discretion and risk.

🤝 Connect with Us

Stay updated and join our community:

📺 Context7 In Media

⭐ Star History

Star History Chart

📄 License

MIT

Available Tools

2 tools
get-library-docsA

Fetches up-to-date documentation for a library. You must call 'resolve-library-id' first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.

ParametersJSON Schema
NameRequiredDescriptionDefault
context7CompatibleLibraryIDYesExact Context7-compatible library ID (e.g., '/mongodb/docs', '/vercel/next.js', '/supabase/supabase', '/vercel/next.js/v14.3.0-canary.87') retrieved from 'resolve-library-id' or directly from user query in the format '/org/project' or '/org/project/version'.
topicNoTopic to focus documentation on (e.g., 'hooks', 'routing').
tokensNoMaximum number of tokens of documentation to retrieve (default: 10000). Higher values provide more context but consume more tokens.

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It mentions the need for a 'Context7-compatible library ID' and implies it fetches documentation, but lacks details on behavioral traits like rate limits, error handling, or what 'up-to-date' means. It adds some context (e.g., ID format requirements) but is incomplete for a tool with no annotation coverage.

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 concise and front-loaded: it starts with the core purpose, then immediately provides critical usage guidelines. Both sentences are essential—the first defines the tool, and the second explains prerequisites—with no wasted words, making it highly 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 no annotations and no output schema, the description is moderately complete. It covers the purpose and usage well but lacks details on behavior (e.g., response format, errors) and output. For a tool with 3 parameters and no structured safety hints, it should do more to compensate, leaving gaps in contextual understanding.

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 parameters thoroughly. The description adds minimal value beyond the schema by mentioning the ID format and prerequisite, but doesn't provide additional semantics for parameters like 'topic' or 'tokens'. Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Fetches up-to-date documentation for a library.' It specifies the resource (library documentation) and the action (fetching). However, it doesn't explicitly differentiate from the sibling 'resolve-library-id' beyond mentioning it as a prerequisite, so it falls short of a perfect 5.

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 vs. alternatives: it states that 'resolve-library-id' must be called first unless the user provides a library ID directly. This clearly defines the prerequisite and alternative scenarios, making it easy for an agent to decide when to invoke this tool.

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

resolve-library-idA

Resolves a package/product name to a Context7-compatible library ID and returns a list of matching libraries.

You MUST call this function before 'get-library-docs' to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.

Selection Process:

  1. Analyze the query to understand what library/package the user is looking for

  2. Return the most relevant match based on:

  • Name similarity to the query (exact matches prioritized)

  • Description relevance to the query's intent

  • Documentation coverage (prioritize libraries with higher Code Snippet counts)

  • Trust score (consider libraries with scores of 7-10 more authoritative)

Response Format:

  • Return the selected library ID in a clearly marked section

  • Provide a brief explanation for why this library was chosen

  • If multiple good matches exist, acknowledge this but proceed with the most relevant one

  • If no good matches exist, clearly state this and suggest query refinements

For ambiguous queries, request clarification before proceeding with a best-guess match.

ParametersJSON Schema
NameRequiredDescriptionDefault
libraryNameYesLibrary name to search for and retrieve a Context7-compatible library ID.

TDQS

A4.2/5.0
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 tool's behavior: it returns a list of matching libraries, explains the selection process (prioritizing exact matches, description relevance, documentation coverage, trust score), and outlines the response format (including handling of multiple matches, no matches, and ambiguous queries). However, it doesn't mention potential limitations like rate limits or authentication needs, which keeps it from a perfect score.

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

Conciseness3/5

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

The description is front-loaded with the core purpose and usage guidelines, but it includes extensive procedural details (e.g., 'Selection Process' and 'Response Format' sections) that, while informative, make it verbose. Some sentences, like those detailing the selection criteria, could be more concise. It earns its place but could be streamlined for better 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 a selection process and response formatting) and the absence of annotations and output schema, the description does a good job of covering key aspects: purpose, usage, behavior, and response handling. However, it lacks details on error cases beyond 'no good matches' and doesn't specify the exact structure of the returned list, leaving some gaps in completeness for a tool with no 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?

The schema description coverage is 100%, with the parameter 'libraryName' well-documented as 'Library name to search for and retrieve a Context7-compatible library ID.' The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to.

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's purpose: 'Resolves a package/product name to a Context7-compatible library ID and returns a list of matching libraries.' It uses specific verbs ('resolves', 'returns') and distinguishes from its sibling 'get-library-docs' by explaining this is a prerequisite step. The purpose is unambiguous and well-articulated.

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 usage guidelines: 'You MUST call this function before 'get-library-docs' to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.' It clearly states when to use this tool versus alternatives (direct ID usage) and references the sibling tool, making the guidance comprehensive and actionable.

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

TDQS

A4.1/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: 'resolve-library-id' resolves package names to library IDs, while 'get-library-docs' fetches documentation using those IDs. There is no overlap in functionality, and the descriptions explicitly define their roles and interdependencies, making it impossible to confuse them.

Naming Consistency5/5

Both tools follow a consistent verb-noun pattern with kebab-case (e.g., 'get-library-docs', 'resolve-library-id'), using clear action verbs ('get', 'resolve') paired with specific nouns. This consistency makes the tool set predictable and easy to understand at a glance.

Tool Count3/5

With only two tools, the server feels thin for its apparent domain of library documentation retrieval. While the tools cover core functions (resolving IDs and fetching docs), typical documentation servers might include additional operations like searching, listing libraries, or managing versions, suggesting a borderline under-scoped surface.

Completeness4/5

The tool set covers the essential workflow for fetching library documentation: resolving IDs and retrieving docs. However, there are minor gaps, such as no tools for searching libraries directly, listing available libraries, or handling documentation updates, which agents might need to work around but don't break core functionality.

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