Fuel Network & Sway Language
Semantic search for Fuel Network and Sway Language documentation using a local vector database.
Fuel Network & Sway Language MCP Server
This project provides a Model Context Protocol (MCP) server for the Fuel Network and Sway Language ecosystem. It allows IDEs (like Cursor) to search and interact with Fuel documentation directly within the development environment.
The server indexes Fuel and Sway documentation into a local Vectra vector database using open-source embeddings (via Transformers.js) for powerful semantic search capabilities.
Features
- Local semantic search of docs.fuel.network content
- No Docker dependency - runs with just Bun
- Fast file-based vector storage with Vectra
- Enhanced result filtering and formatting
- Hybrid search with keyword fallback
Quick Install
# Clone the repo
git clone https://github.com/FuelLabs/fuel-mcp-server
cd fuel-mcp-server
# Install dependencies
bun install
# Index documentation
bun run src/indexer.ts ./docs
# Test search
bun run src/query.ts --run "What is FuelVM?"
# Start MCP server
bun run src/cli.ts
Usage
STDIO Transport (Default)
bun run src/cli.ts
# or explicitly
bun run src/cli.ts --transport stdio
HTTP Transport
bun run src/cli.ts --transport http --port 3500
# Server runs at http://127.0.0.1:3500/mcp
# Health check: http://127.0.0.1:3500/health
CLI Options
bun run src/cli.ts --help
bun run src/cli.ts --transport http --port 3500
bun run src/cli.ts --transport stdio
Claude/Cursor Integration
Add to your MCP config file:
{
"mcpServers": {
"fuel-server": {
"command": "bun",
"args": ["run", "/absolute/path/to/fuel-mcp-server/src/cli.ts", "--transport", "stdio"]
}
}
}
Project Structure
.
├── docs/ # Markdown documentation files
├── src/
│ ├── cli.ts # Main CLI entry point
│ ├── server.ts # MCP server factory
│ ├── transports/
│ │ ├── stdio.ts # STDIO transport
│ │ └── http.ts # HTTP transport
│ ├── chunker.ts # Markdown chunking logic
│ ├── indexer.ts # Document indexing script
│ ├── query.ts # Search query script
│ └── *.test.ts # Test files
├── vectra_index/ # Local vector database (created after indexing)
├── package.json
└── README.md
Prerequisites
- Bun: Install from bun.sh
Usage
1. Index Documents
Place markdown files in ./docs or specify a different directory:
# Index docs in ./docs (default)
bun run src/indexer.ts
# Index custom directory
bun run src/indexer.ts /path/to/your/docs
# With custom settings
EMBEDDING_MODEL=Xenova/bge-small-en-v1.5 bun run src/indexer.ts ./docs
2. Search Documents
# Basic search
bun run src/query.ts --run "What is the FuelVM?"
# Custom number of results
NUM_RESULTS=10 bun run src/query.ts --run "smart contracts"
3. Run MCP Server
# Start MCP server (stdio-mode)
bun run src/cli.ts
# With HTTP transport
bun run src/cli.ts --transport http --port 3500
4. Run Tests
bun test
Environment Variables
| Variable | Default | Description |
|---|---|---|
VECTRA_INDEX_PATH | ./vectra_index | Vector database location |
EMBEDDING_MODEL | Xenova/all-MiniLM-L6-v2 | Hugging Face model |
CHUNK_SIZE | 2000 | Target tokens per chunk |
NUM_RESULTS | 5 | Search results count |
LOG_LEVEL | Set to debug for verbose output |
Implementation Details
- Chunking: Preserves code blocks, splits by paragraphs with context awareness
- Indexing: Generates embeddings with enhanced metadata for better search
- Querying: Semantic search with quality filtering and keyword fallback
- MCP Server: Exposes search as tool via stdio communication
- Storage: File-based Vectra index (no external database required)
API
MCP Tools
searchFuelDocs
query(string): Search querynResults(number, optional): Number of results (default: 5)includeScore(boolean, optional): Include relevance scores
provideStdContext
- Returns Sway standard library paths and types
Development
# Install dependencies
bun install
# Run tests
bun test
# Index sample docs
bun run src/indexer.ts ./docs
# Test search functionality
bun run src/query.ts --run "test query"
# Start MCP server for development (STDIO)
bun run src/cli.ts
# Start MCP server for development (HTTP)
bun run src/cli.ts --transport http --port 3500
相关服务器
Library Docs MCP Server
Search and fetch documentation for popular libraries like Langchain, Llama-Index, and OpenAI using the Serper API.
Brave Search
Integrates the Brave Search API for both web and local search capabilities. Requires a BRAVE_API_KEY.
Wikipedia MCP
A remote MCP server for Wikipedia.
BudgetFitter
BudgetFitter is a free UK deal discovery platform with a public MCP server. Search verified discount codes, look up brand intelligence, and navigate deals — no auth required.
Bocha
A search engine for AI applications, providing world knowledge from web pages and various content sources like weather, news, and images.
CryptoPanic News
Provides the latest cryptocurrency news to AI agents, powered by the CryptoPanic API.
Korea Tourism API MCP Server
Search for South Korean tourism information, including festivals, temples, and restaurants, using the official Korea Tourism Organization API.
Semiconductor Supply Chain MCP Server
Access semiconductor B2B platforms like AnySilicon and DesignReuse for IP core and ASIC service procurement.
Jina AI Search
Access Jina AI's Search Foundation APIs for web search, news search, and more, tailored for LLMs.
Enhanced PubMed Search
A search server for PubMed, the biomedical literature database, using a pure Node.js implementation.