Clarity MCP Bootleg Market
Description
# Clarity MCP Bootleg Market Turn browser traffic into tool calls. Smuggle your network requests into an MCP. ## What's This All About? Clarity is where you come when you need to get your hands on some Model Context Protocols (MCPs). Our server connects AI assistants like Claude…
About
# Clarity MCP Bootleg Market Turn browser traffic into tool calls. Smuggle your network requests into an MCP. ## What's This All About? Clarity is where you come when you need to get your hands on some Model Context Protocols (MCPs). Our server connects AI assistants like Claude with web APIs extracted from your HAR…
Details
- Author
- theclarityproject
- Downloads
- 234
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- Extracts API endpoints from HAR files automatically
- Generates MCP tools using AI from captured traffic
- Forwards ListTools and CallTool requests to a backend
- Transforms responses to match the MCP protocol
- Requires only an API key for authentication
- Integrates directly with Claude Desktop via stdio
Install globally with npm install -g @lekt9/clarity-mcp, set the CLARITY_API_KEY environment variable (and optionally CLARITY_MCP_ID), then run clarity-mcp. For Claude Desktop, use the command npx -y @smithery/cli@latest install @lekt9/clarity-mcp --claude. Create your own MCPs by uploading a HAR file at https://www.theclarityproject.net and obtaining an API key.
Clarity MCP Bootleg Market
Turn browser traffic into tool calls. Smuggle your network requests into an MCP.
What's This All About?
Clarity is where you come when you need to get your hands on some Model Context Protocols (MCPs). Our server connects AI assistants like Claude with web APIs extracted from your HAR files. Think of it as a way to "borrow" functionality from websites and turn it into something AI can use.
How It Works
sequenceDiagram
participant Client as MCP Client (Claude)
participant Server as Clarity Server
participant Backend as Clarity Backend
participant API as Target Web APIs
note over Client,API: HAR File Processing
Backend->>Backend: Process HAR file
Backend->>Backend: Extract API endpoints
Backend->>Backend: Generate tools with AI
Backend->>Backend: Store in database
note over Client,API: Runtime Flow
Client->>Server: Connect via stdio
Client->>Server: ListTools request
Server->>Backend: Forward request
Backend->>Server: Return available tools
Server->>Client: Deliver tools to client
Client->>Server: CallTool request
Server->>Server: Transform tool name
Server->>Backend: Forward to backend
Backend->>API: Execute API call
API->>Backend: Return response
Backend->>Server: Return result
Server->>Client: Deliver to client
Installation
```bash
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