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    Seta Mcp

    MCP server powered by local documentation

    1 stars
    TypeScript
    Updated Jun 14, 2025
    local
    mcp
    mcp-server
    model-context-protocol
    offline

    Table of Contents

    • Why use this?
    • 💡 How It Works?
    • 🛠️ Getting Started
    • Requirements
    • Local Documentation Structure
    • Enhanced manifest.json Format
    • 🔍 Semantic Search with seta-indexer
    • Development
    • Local Configuration Example (for development)
    • Testing with MCP Inspector
    • Disclaimer
    • License

    Table of Contents

    • Why use this?
    • 💡 How It Works?
    • 🛠️ Getting Started
    • Requirements
    • Local Documentation Structure
    • Enhanced manifest.json Format
    • 🔍 Semantic Search with seta-indexer
    • Development
    • Local Configuration Example (for development)
    • Testing with MCP Inspector
    • Disclaimer
    • License

    Documentation

    Seta MCP - Up-to-date Local Docs for Coding

    Assist Salesforce developers to create code and configuration! This is a MCP server that you can run locally or host remotely.

    Designed to fetch documentation from your local file system, giving you complete control over the context provided to your AI assistant.

    Inspired by context7 - but this application uses local documentation library.

    Why use this?

    Seta MCP server consists of three primary components:

    • MCP server code (this repository)
    • Open / public, internal or proprietary documentation for Apex, LWC, configuration etc.
    • NEW: Semantic search indexer for intelligent document discovery

    Seta MCP helps you to -

    • Work entirely offline.
    • Have fine-grained control over the exact documentation versions and content.
    • Quickly iterate on documentation and have it immediately available to your LLM.
    • NEW: Find relevant documentation using semantic search, even when exact keywords don't match.

    💡 How It Works?

    This MCP server reads documentation from a local directory structure you define.

    1. **Set LOCAL_DOCS_PATH**: You specify a root directory for your documentation via the LOCAL_DOCS_PATH environment variable.

    2. Organize Libraries: Inside LOCAL_DOCS_PATH, each library or documentation set should reside in its own subdirectory.

    3. **Enhanced manifest.json: Each library subdirectory must** contain a manifest.json file with rich metadata including difficulty levels, use cases, learning paths, and semantic groups.

    4. Optional Semantic Indexing: Run seta-indexer to create a vector database for semantic search capabilities.

    When you prompt your LLM (e.g., in VSCode) with use latest Apex docs, use seta or just reference any of the below tools in the prompt:

    • The get-library-id tool searches the manifest.json files in your LOCAL_DOCS_PATH to find matching libraries.
    • The get-library-docs tool then fetches the content of the specified document file from your local file system.

    🛠️ Getting Started

    Requirements

    • Node.js >= v18.0.0
    • VSCode, Cursor, Windsurf, Claude Desktop, or another MCP Client.
    • A local directory containing your documentation, structured as described below.
    • The LOCAL_DOCS_PATH environment variable must be set to point to this directory.

    Local Documentation Structure

    Your LOCAL_DOCS_PATH should point to a root directory. Inside this, each library has its own folder:

    code
    /
    ├── my-awesome-lib/
    │   ├── manifest.json
    │   ├── main_guide.md
    │   ├── .seta_lancedb/          # Created by seta-indexer (optional)
    │   └── topics/
    │       └── report.md
    │       └── advanced_reports.txt
    └── another-tool/
        ├── manifest.json
        └── quick_start.md

    Enhanced manifest.json Format

    Each library directory (e.g., my-awesome-lib/) must contain a manifest.json file in the following enhanced format:

    json
    {
      "name": "My Awesome Library",
      "description": "A brief description of what this library does.",
      "version": "2.1.0",
      "default_doc": "main_guide.md", // File to use if no topic is specified
      "topics": [
        {
          "name": "report",
          "file": "report.md",
          "tags": ["report"],
          "related": ["advanced"],
          "prerequisites": [],
          "leads_to": ["advanced"],
          "difficulty": "beginner",
          "use_cases": ["basic reporting", "data visualization"],
          "code_patterns": ["SOQL queries", "report types"]
        },
        {
          "name": "advanced",
          "file": "topics/advanced_reports.txt",
          "tags": ["advanced"],
          "related": ["report"],
          "prerequisites": ["report"],
          "leads_to": [],
          "difficulty": "advanced",
          "use_cases": ["complex analytics", "custom report types"],
          "code_patterns": ["dynamic SOQL", "custom report builders"]
        }
      ],
      "semantic_groups": {
        "fundamentals": ["report"],
        "advanced_features": ["advanced"]
      },
      "learning_paths": {
        "beginner": ["report"],
        "expert": ["report", "advanced"]
      },
      "totalSnippets": 25 // Optional: for display purposes
    }

    Enhanced topic properties:

    • prerequisites (array of strings, optional): Topics that should be understood first
    • leads_to (array of strings, optional): Topics that naturally follow this one
    • difficulty (string, optional): "beginner", "intermediate", or "advanced"
    • use_cases (array of strings, optional): Practical applications of this topic
    • code_patterns (array of strings, optional): Code patterns or techniques covered

    New library-level properties:

    • semantic_groups (object, optional): Named collections of related topics
    • learning_paths (object, optional): Suggested sequences of topics for different skill levels

    How enhanced topic lookup works:

    • When searching, the server matches your query against library name, description, topic names, tags, use_cases, and code_patterns.
    • When fetching documentation for a topic, the server automatically includes context from prerequisites, related topics, and next steps.
    • You can request entire semantic groups or learning paths by name.

    🔍 Semantic Search with seta-indexer

    Development

    Clone the project and install dependencies:

    bash
    npm i

    Build (assuming main.ts is in the root and tsconfig.json is configured for outDir: "./dist" and rootDir: "./"):

    bash
    npm run build

    This will compile main.ts (and files in lib/ and indexer/) to dist/main.js and dist/indexer/cli.js.

    Local Configuration Example (for development)

    To run your local development version with an MCP client like Cursor:

    json
    {
      "mcpServers": {
        "seta_dev": {
          "command": "npx",
          "args": ["tsx", "/path/to/your/project/dist/main.js"],
          "env": {
            "LOCAL_DOCS_PATH": "/absolute/path/to/your/test_documentation_root", // Essential for testing
            "DEFAULT_MAX_TOKENS": "5000" // Optional
          }
        }
      }
    }

    Testing with MCP Inspector

    Ensure LOCAL_DOCS_PATH is set in your environment.

    bash
    # For published version
    # export LOCAL_DOCS_PATH="/path/to/your/docs"
    npx -y @modelcontextprotocol/inspector npx seta-mcp@latest

    Disclaimer

    This project relies on the documentation you provide. The quality, accuracy, and completeness of the generated context are directly dependent on your local documentation files. Use at your own discretion and risk.

    License

    MIT

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