Context7 MCP Server
Allows use of OpenAI as an LLM provider for code analysis and generation tasks.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Context7 MCP Serveranalyze my code for performance issues"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Context7 MCP Server
This is the Context7 MCP Server, designed to integrate with the Context7 system and provide LLM capabilities through the Model Context Protocol (MCP). This server enables seamless integration with popular IDEs and coding assistants.
Features
MCP Protocol Support: Full Model Context Protocol implementation for IDE integration
Multi-IDE Compatibility: Works with Cursor, Claude Desktop, Windsurf, and more
Universal LLM Integration: Supports multiple LLM providers (Gemini, OpenAI, etc.)
Code Analysis Tools: Built-in tools for code analysis, generation, and debugging
Context Management: Advanced context gathering and formatting
Reasoning Strategies: Dynamic reasoning modes for different use cases
Related MCP server: VSCode Language Server MCP Extension
IDE Integration
Cursor IDE
Install the server:
cd TesterBud npm install npm run buildConfigure in Cursor:
Open Cursor Settings → MCP
Add new MCP server:
{ "mcpServers": { "context7": { "command": "node", "args": ["/absolute/path/to/TesterBud/dist/mcp-server.js"], "env": { "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY" } } } }
Claude Desktop
Copy configuration:
cp claude_desktop_config.json ~/Library/Application\ Support/Claude/claude_desktop_config.json # On Windows: copy to %APPDATA%/Claude/claude_desktop_config.json # On Linux: copy to ~/.config/Claude/claude_desktop_config.jsonEdit the configuration with your actual paths and API key.
Windsurf
Add to Windsurf settings:
{ "mcp_servers": { "context7": { "command": "node", "args": ["/absolute/path/to/TesterBud/dist/mcp-server.js"], "env": { "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY" } } } }
Generic MCP Client
Use the .mcp.json configuration file provided in the root directory as a template for any MCP-compatible client.
Available Tools
The server provides the following MCP tools:
analyze_code: Analyze code for patterns, issues, and improvementsgenerate_code: Generate code based on requirementsdebug_code: Debug code issues and provide solutionsget_context: Get relevant context and documentation
Setup
Clone the repository:
git clone <repository-url> cd TesterBudInstall dependencies:
npm installConfigure environment variables: Copy
.env.exampleto.envand fill in your API keys:cp .env.example .envEdit
.env:GEMINI_API_KEY=YOUR_GEMINI_API_KEY
Running the Server
MCP Mode (for IDE integration)
# Development
npm run mcp:dev
# Production
npm run build
npm run mcpHTTP API Mode (for web applications)
# Development
npm run dev
# Production
npm run build
npm startDocker
docker-compose up --buildTesting the MCP Server
Test with MCP Inspector
npm install -g @modelcontextprotocol/inspector
mcp-inspector node dist/mcp-server.jsTest with curl (HTTP mode)
curl -X POST http://localhost:3000/mcp/create-session \
-H "Content-Type: application/json" \
-d '{"userId": "test-user"}'Deployment
Refer to render.yaml for Render deployment configuration.
Deployment scripts for GCP and Docker are available in the deploy/ directory.
Configuration Files
.mcp.json: Generic MCP configuration templateclaude_desktop_config.json: Claude Desktop specific configurationrender.yaml: Render deployment configurationdocker-compose.yml: Docker deployment configuration
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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MCP directory API
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curl -X GET 'https://glama.ai/api/mcp/v1/servers/Mapileon2/TesterBud-MCP'
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