📋 Table of Contents

📖 Introduction

GitHub to MCP bridges the gap between code repositories and AI assistants. Instead of manually describing APIs or copying code snippets into chat windows, this tool generates a standardized interface that allows AI systems to programmatically explore, read, and interact with any GitHub repository.

The generated MCP servers provide tools that AI assistants can invoke to read files, search code, list directory structures, and call API endpoints discovered within the repository. This enables AI assistants to have deep, structured access to codebases without requiring manual context management.

┌─────────────────────────────────────────────────────────────┐
│                     GitHub Repository                       │
└─────────────────────────────────────────────────────────────┘
                              ↓
┌─────────────────────────────────────────────────────────────┐
│  1. Fetch & Classify  →  Detect repo type (API/CLI/Lib)     │
│  2. Extract Tools     →  OpenAPI, GraphQL, Code, README     │
│  3. Generate Server   →  TypeScript or Python MCP server    │
│  4. Bundle Output     →  Complete package with dependencies │
└─────────────────────────────────────────────────────────────┘
                              ↓
┌─────────────────────────────────────────────────────────────┐
│              Ready-to-use MCP Server + Config               │
└─────────────────────────────────────────────────────────────┘

🔌 What is MCP

The Model Context Protocol (MCP) is an open standard developed by Anthropic that defines how AI assistants communicate with external tools and data sources. MCP servers expose "tools" that AI models can invoke, along with "resources" that provide context and "prompts" that guide interactions.

When you connect an MCP server to an AI assistant like Claude Desktop, the assistant gains the ability to call the tools defined by that server. For example, a GitHub MCP server might expose tools like read_file, search_code, or list_pull_requests, which the AI can invoke to gather information needed to answer questions or complete tasks.

This project generates MCP servers from GitHub repositories, automatically creating tools based on the repository's contents, APIs, and documentation.

🚀 Quick Start

🌐 Web UI (Easiest)

Visit github-to-mcp.vercel.app — Paste any GitHub URL, click Generate, download your MCP server.

💻 CLI (One Command)

npx @nirholas/github-to-mcp https://github.com/stripe/stripe-node

📦 Programmatic (For Automation)

import { generateFromGithub } from '@nirholas/github-to-mcp';

const result = await generateFromGithub('https://github.com/stripe/stripe-node');
console.log(`Generated ${result.tools.length} tools`);
await result.save('./my-mcp-server');

✨ Features

🔬 Repository Analysis

  • Automatic repository type classification (API, library, CLI tool, MCP server, documentation)
  • Detection and parsing of OpenAPI/Swagger specifications
  • GraphQL schema extraction and query/mutation tool generation
  • gRPC/Protobuf service definition parsing
  • AsyncAPI specification support for event-driven APIs
  • Source code analysis for function extraction

🌍 Multi-Language Support

Input repositories:

  • TypeScript and JavaScript
  • Python
  • Go
  • Java and Kotlin
  • Rust
  • Ruby
  • C# and F#

Output MCP servers:

  • TypeScript (using the official MCP SDK)
  • Python (using the MCP Python SDK)
  • Go (using community MCP libraries)

🔧 Tool Extraction

  • OpenAPI endpoints become callable tools with typed parameters
  • GraphQL queries and mutations become tools with input validation
  • Python functions decorated with @mcp.tool are preserved
  • CLI commands documented in READMEs become executable tools
  • HTTP route handlers from popular frameworks are detected

⚡ Code Generation

  • Complete, runnable MCP server code with all dependencies
  • Configuration files for Claude Desktop, Cursor, and other clients
  • Docker deployment templates
  • TypeScript type definitions for all generated tools

📥 Installation

From Source

Clone the repository and install dependencies:

git clone https://github.com/nirholas/github-to-mcp.git
cd github-to-mcp
pnpm install
pnpm build

Using the Web Interface

The web application is deployed at github-to-mcp.vercel.app. Use the browser-based interface without any local installation.

📖 Usage

🌐 Web Interface

The web interface provides the simplest way to convert repositories:

  1. Navigate to the web application
  2. Enter a GitHub repository URL (e.g., https://github.com/owner/repo)
  3. Optionally configure extraction options
  4. Click "Generate" to analyze the repository
  5. Review the generated tools and code
  6. Download the MCP server package or copy the configuration

The web interface also provides an interactive playground where you can test generated tools before downloading.

💻 Command Line Interface

After building the project locally, you can use the CLI:

# Basic usage
node packages/core/dist/cli.mjs https://github.com/owner/repo

# Specify output directory
node packages/core/dist/cli.mjs https://github.com/owner/repo --output ./my-mcp-server

# Generate Python instead of TypeScript
node packages/core/dist/cli.mjs https://github.com/owner/repo --language python

# Include only specific extraction sources
node packages/core/dist/cli.mjs https://github.com/owner/repo --sources openapi,readme

# Use a GitHub token for private repos or higher rate limits
GITHUB_TOKEN=ghp_xxx node packages/core/dist/cli.mjs https://github.com/owner/repo

📦 Programmatic API

Import the generator in your own TypeScript or JavaScript code:

import { GithubToMcpGenerator } from '@nirholas/github-to-mcp';

const generator = new GithubToMcpGenerator({
  githubToken: process.env.GITHUB_TOKEN,
  sources: ['openapi', 'readme', 'code'],
  outputLanguage: 'typescript'
});

const result = await generator.generate('https://github.com/owner/repo');

console.log(`Repository: ${result.name}`);
console.log(`Classification: ${result.classification.type}`);
console.log(`Generated ${result.tools.length} tools`);

// Access the generated code
console.log(result.code);

// Save to disk
await result.save('./output-directory');

interface GithubToMcpOptions {
  // GitHub personal access token for API authentication
  githubToken?: string;
  
  // Which sources to extract tools from
  // Default: ['openapi', 'readme', 'code', 'graphql', 'mcp']
  sources?: Array<'openapi' | 'readme' | 'code' | 'graphql' | 'grpc' | 'mcp'>;
  
  // Output language for generated server
  // Default: 'typescript'
  outputLanguage?: 'typescript' | 'python' | 'go';
  
  // Include universal tools (read_file, list_files, etc.)
  // Default: true
  includeUniversalTools?: boolean;
  
  // Maximum number of tools to generate
  // Default: 100
  maxTools?: number;
  
  // Specific branch to analyze
  // Default: repository's default branch
  branch?: string;
}

⚙️ How It Works

The conversion process follows these stages:

🏷️ Repository Classification

The generator first analyzes the repository to determine its type and structure:

  1. Fetch repository metadata from the GitHub API
  2. Download and parse the README file
  3. Examine package.json, setup.py, go.mod, or other manifest files
  4. Scan for API specification files (openapi.json, schema.graphql, etc.)
  5. Classify the repository as one of:
Classification Description
mcp-server An existing MCP server implementation
api-sdk A client library for an API
cli-tool A command-line application
library A general-purpose code library
documentation Primarily documentation content
data Data files or datasets
unknown Unclassified repository

Classification influences which extraction strategies are prioritized and how tools are named.

🔍 Tool Extraction

Tools are extracted from multiple sources within the repository:

When an OpenAPI specification is found:

  1. Parse the specification (JSON or YAML, v2 or v3)
  2. Extract each endpoint as a potential tool
  3. Convert path parameters, query parameters, and request bodies to tool input schemas
  4. Generate descriptions from operation summaries and descriptions
  5. Map HTTP methods to appropriate tool semantics

When GraphQL schemas are found:

  1. Parse .graphql or .gql schema files
  2. Extract Query type fields as read-only tools
  3. Extract Mutation type fields as write tools
  4. Convert GraphQL input types to JSON Schema for tool inputs
  5. Handle nested types and custom scalars

The README is analyzed for:

  1. Code blocks showing CLI usage patterns
  2. API endpoint examples with curl or fetch
  3. Function call examples with parameters
  4. Installation and usage instructions

Extracted examples become tools with inferred parameter schemas.

For supported languages, the source code is analyzed:

  1. Python: Functions decorated with @mcp.tool, @server.tool, or similar
  2. TypeScript: Exported functions with JSDoc annotations
  3. Go: HTTP handlers from Gin, Echo, Chi, Fiber, or Gorilla Mux
  4. Java/Kotlin: Methods annotated with @GetMapping, @PostMapping, etc.
  5. Rust: Route handlers from Actix-web, Axum, or Rocket

If the repository is already an MCP server:

  1. Detect server.tool() definitions
  2. Extract tool names, descriptions, and schemas
  3. Preserve existing tool implementations where possible

🏗️ Code Generation

After tools are extracted, the generator produces:

  1. A main server file implementing the MCP protocol
  2. Tool handler functions for each extracted tool
  3. Type definitions for all input and output schemas
  4. A package.json or equivalent with required dependencies
  5. Configuration files for popular MCP clients
  6. Optional Docker deployment files

The generated code is complete and runnable without modification.

🛠️ Generated Tools

🌐 Universal Tools

Every generated MCP server includes these baseline tools for repository exploration:

Tool Description Parameters
get_readme Retrieve the repository's README content None
list_files List files and directories at a given path path (optional, defaults to root)
read_file Read the contents of a specific file path (required)
search_code Search for patterns across the repository query (required), path (optional)

These tools ensure that even if no APIs or functions are detected, the AI assistant can still explore and understand the repository.

🔧 Extracted Tools

Additional tools are generated based on repository contents:

From OpenAPI Specifications

Each API endpoint becomes a tool:

POST /users      →  create_user(name: string, email: string)
GET /users/{id}  →  get_user(id: string)
PUT /users/{id}  →  update_user(id: string, name?: string, email?: string)
DELETE /users/{id} →  delete_user(id: string)
GET /users       →  list_users(page?: number, limit?: number)

From GraphQL Schemas

Queries and mutations become tools:

type Query {
  user(id: ID!): User         →  get_user(id: string)
  users(first: Int): [User]   →  list_users(first?: number)
}

type Mutation {
  createUser(input: CreateUserInput!): User  →  create_user(input: object)
}

From Python Code

@server.tool()
async def analyze_sentiment(text: str) -> str:
    """Analyze the sentiment of the given text."""
    # Implementation

Becomes: analyze_sentiment(text: string) → "Analyze the sentiment of the given text."

From README Examples

CLI commands documented in READMEs:

# Create a new project
mycli create --name myproject --template typescript

Becomes: mycli_create(name: string, template?: string)

⚙️ Configuration

🔐 Environment Variables

Variable Description Required
GITHUB_TOKEN GitHub personal access token for API access No (but recommended)
GITHUB_API_URL Custom GitHub API URL for Enterprise No

GitHub Token

Without a token, GitHub API requests are limited to 60 per hour. With a token, the limit increases to 5,000 per hour. For private repositories, a token with appropriate access is required.

Create a token at: https://github.com/settings/tokens

Required scopes:

  • repo (for private repositories)
  • public_repo (for public repositories only)

🎛️ Generator Options

When using the programmatic API, you can configure:

const generator = new GithubToMcpGenerator({
  // Authentication
  githubToken: process.env.GITHUB_TOKEN,
  
  // Extraction sources to enable
  sources: ['openapi', 'readme', 'code', 'graphql', 'grpc', 'mcp'],
  
  // Output configuration
  outputLanguage: 'typescript', // or 'python', 'go'
  
  // Tool filtering
  includeUniversalTools: true,
  maxTools: 100,
  
  // Repository options
  branch: 'main', // specific branch to analyze
});

🤖 Integrating with AI Assistants

Claude Desktop

Add the generated server to your Claude Desktop configuration:

Platform Config Path
macOS ~/Library/Application Support/Claude/claude_desktop_config.json
Windows %APPDATA%\Claude\claude_desktop_config.json 
{
  "mcpServers": {
    "my-repo": {
      "command": "node",
      "args": ["/absolute/path/to/generated/server.mjs"],
      "env": {
        "GITHUB_TOKEN": "ghp_xxxx"
      }
    }
  }
}

⚠️ Restart Claude Desktop after modifying the configuration.

Cursor

Cursor supports MCP servers through its settings. Add the server path in Cursor's MCP configuration panel, or edit the configuration file directly:

{
  "mcp": {
    "servers": {
      "my-repo": {
        "command": "node",
        "args": ["/path/to/server.mjs"]
      }
    }
  }
}

💻 VS Code with Continue

If using the Continue extension for VS Code:

{
  "models": [...],
  "mcpServers": {
    "my-repo": {
      "command": "node",
      "args": ["/path/to/server.mjs"]
    }
  }
}

🔌 Other MCP Clients

Any MCP-compatible client can use the generated servers. The server communicates over stdio by default, accepting JSON-RPC messages on stdin and responding on stdout.

To run manually:

node server.mjs

The server will wait for MCP protocol messages on stdin.

🎮 Interactive Playground

The web application includes an interactive playground for testing generated tools:

  1. After generating tools from a repository, click "Open in Playground"
  2. Select a tool from the list
  3. Fill in the required parameters
  4. Click "Execute" to run the tool
  5. View the JSON response

The playground executes tools in a sandboxed environment and displays results in real-time.

🔗 Sharing Playground Sessions

You can share your generated tools with others:

Parameter Description
?code=<base64> Base64-encoded TypeScript server code
?gist=<id> GitHub Gist ID containing server code
?name=<name> Display name for the server

Example:

https://github-to-mcp.vercel.app/playground?gist=abc123&name=My%20API

📁 Project Structure

github-to-mcp/
├── 📂 apps/
│   ├── 📂 web/                    # Next.js web application
│   │   ├── 📂 app/                # Next.js App Router pages
│   │   │   ├── 📂 api/            # API routes for conversion
│   │   │   ├── 📂 convert/        # Conversion page
│   │   │   ├── 📂 playground/     # Interactive playground
│   │   │   └── 📂 dashboard/      # User dashboard
│   │   ├── 📂 components/         # React components
│   │   ├── 📂 hooks/              # Custom React hooks
│   │   ├── 📂 lib/                # Utility functions
│   │   └── 📂 types/              # TypeScript type definitions
│   └── 📂 vscode/                 # VS Code extension (in development)
│
├── 📂 packages/
│   ├── 📂 core/                   # Main conversion engine
│   │   └── 📂 src/
│   │       ├── index.ts           # GithubToMcpGenerator class
│   │       ├── github-client.ts   # GitHub API client
│   │       ├── readme-extractor.ts    # README parsing
│   │       ├── code-extractor.ts      # Source code analysis
│   │       ├── graphql-extractor.ts   # GraphQL schema parsing
│   │       ├── mcp-introspector.ts    # Existing MCP server detection
│   │       ├── python-generator.ts    # Python output generation
│   │       ├── go-generator.ts        # Go output generation
│   │       └── types.ts               # Type definitions
│   │
│   ├── 📂 openapi-parser/         # OpenAPI specification parser
│   │   └── 📂 src/
│   │       ├── parser.ts          # OpenAPI parsing logic
│   │       ├── analyzer.ts        # Endpoint analysis
│   │       ├── transformer.ts     # Schema transformation
│   │       └── generator.ts       # Tool generation
│   │
│   ├── 📂 mcp-server/             # MCP server utilities
│   │   └── 📂 src/
│   │       ├── server.ts          # Base MCP server implementation
│   │       └── tools.ts           # Tool registration helpers
│   │
│   └── 📂 registry/               # Tool registry management
│       └── 📂 src/
│           └── index.ts           # Registry operations
│
├── 📂 mkdocs/                     # Documentation site (MkDocs)
│   ├── 📂 docs/                   # Markdown documentation
│   └── mkdocs.yml                 # MkDocs configuration
│
├── 📂 tests/                      # Integration tests
│   ├── 📂 fixtures/               # Test fixture repositories
│   │   ├── 📂 express-app/        # Express.js test app
│   │   ├── 📂 fastapi-app/        # FastAPI test app
│   │   ├── 📂 graphql/            # GraphQL test schemas
│   │   └── 📂 openapi/            # OpenAPI test specs
│   └── 📂 integration/            # Integration test files
│
├── 📂 templates/                  # Code generation templates
│   ├── Dockerfile.python.template
│   └── Dockerfile.typescript.template
│
├── package.json                   # Root package configuration
├── pnpm-workspace.yaml            # pnpm workspace configuration
├── tsconfig.json                  # TypeScript configuration
└── vitest.config.ts               # Test configuration

🔨 Development

Prerequisites

Requirement Version
Node.js 22.x or later
pnpm 10.x or later
Git 2.x or later

Local Setup

# Clone the repository
git clone https://github.com/nirholas/github-to-mcp.git
cd github-to-mcp

# Install dependencies
pnpm install

# Build all packages
pnpm build

# Start the development server
pnpm dev

The web application will be available at http://localhost:3000.

Building

# Build all packages
pnpm build

# Build specific package
pnpm --filter @nirholas/github-to-mcp build
pnpm --filter @github-to-mcp/openapi-parser build
pnpm --filter web build

Testing

# Run all tests
pnpm test

# Run tests in watch mode
pnpm test:watch

# Run tests with coverage
pnpm test:coverage

# Run specific test file
pnpm test -- tests/integration/openapi-conversion.test.ts

Code Quality

# Run linting
pnpm lint

# Type checking
pnpm typecheck

🏗️ Architecture Overview

The system follows a pipeline architecture:

Input (GitHub URL)
       │
       ▼
┌──────────────────┐
│  GitHub Client   │  Fetches repository metadata, files, and README
└──────────────────┘
       │
       ▼
┌──────────────────┐
│   Classifier     │  Determines repository type and structure
└──────────────────┘
       │
       ▼
┌──────────────────┐
│   Extractors     │  Multiple extractors run in parallel:
│  ├─ OpenAPI      │  • Parse API specifications
│  ├─ GraphQL      │  • Parse GraphQL schemas
│  ├─ README       │  • Extract examples from documentation
│  ├─ Code         │  • Analyze source code
│  └─ MCP          │  • Detect existing MCP tools
└──────────────────┘
       │
       ▼
┌──────────────────┐
│  Deduplicator    │  Removes duplicate tools, merges similar ones
└──────────────────┘
       │
       ▼
┌──────────────────┐
│   Validator      │  Validates tool schemas, adds confidence scores
└──────────────────┘
       │
       ▼
┌──────────────────┐
│   Generator      │  Produces output code in target language
└──────────────────┘
       │
       ▼
Output (MCP Server Code + Configuration)

Each extractor produces a list of ExtractedTool objects with a standardized schema. The deduplicator and validator ensure consistency before the generator produces the final output.

📥 Supported Input Formats

API Specifications

Format File Patterns Version Support
OpenAPI openapi.json, openapi.yaml, swagger.json, swagger.yaml, api.json, api.yaml 2.0, 3.0.x, 3.1.x
GraphQL schema.graphql, *.gql, schema.json June 2018 spec
gRPC *.proto proto3
AsyncAPI asyncapi.json, asyncapi.yaml 2.x

Source Code Languages

Language Framework Detection
TypeScript/JavaScript Express, Fastify, Hono, Next.js API routes
Python FastAPI, Flask, Django REST, MCP SDK decorators
Go Gin, Echo, Chi, Fiber, Gorilla Mux
Java Spring Boot, JAX-RS, Micronaut
Kotlin Ktor, Spring Boot
Rust Actix-web, Axum, Rocket
Ruby Rails, Sinatra, Grape

📤 Output Formats

TypeScript Server

The default output is a TypeScript MCP server using the official @modelcontextprotocol/sdk package:

import { Server } from '@modelcontextprotocol/sdk/server/index.js';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';

const server = new Server({
  name: 'generated-server',
  version: '1.0.0',
}, {
  capabilities: {
    tools: {},
  },
});

server.setRequestHandler(ListToolsRequestSchema, async () => ({
  tools: [/* generated tools */],
}));

server.setRequestHandler(CallToolRequestSchema, async (request) => {
  // Tool dispatch logic
});

const transport = new StdioServerTransport();
await server.connect(transport);

Python Server

Python output uses the MCP Python SDK:

from mcp.server import Server
from mcp.server.stdio import stdio_server

server = Server("generated-server")

@server.tool()
async def example_tool(param: str) -> str:
    """Tool description."""
    # Implementation
    
async def main():
    async with stdio_server() as (read_stream, write_stream):
        await server.run(read_stream, write_stream)

if __name__ == "__main__":
    import asyncio
    asyncio.run(main())

Configuration Files

Each generated server includes:

File Description
claude_desktop_config.json Claude Desktop configuration snippet
cursor_config.json Cursor editor configuration
package.json or requirements.txt Dependencies
Dockerfile (optional) Container deployment

⚠️ Limitations

  • Unauthenticated requests: 60 per hour
  • Authenticated requests: 5,000 per hour
  • Large repositories may require multiple API calls

Provide a GITHUB_TOKEN to increase rate limits.

  • Very large repositories (>1GB) may time out during analysis
  • Repositories with thousands of files may hit API limits
  • Consider analyzing specific subdirectories for monorepos
  • OpenAPI specs produce the most accurate tools
  • README extraction relies on consistent documentation formatting
  • Source code analysis may miss dynamically defined routes
  • Confidence scores indicate extraction reliability
  • TypeScript output is the most mature
  • Python output is functional but may require minor edits
  • Go output is experimental

🔧 Troubleshooting

Provide a GitHub token:

export GITHUB_TOKEN=ghp_xxxxxxxxxxxx
  • Verify the URL is correct
  • For private repositories, ensure your token has repo scope
  • Check that the repository exists and is accessible
  • Verify the repository contains API definitions or documented endpoints
  • Try enabling all extraction sources: --sources openapi,readme,code,graphql,mcp
  • Check that specification files follow standard naming conventions
  • Ensure Node.js 22+ is installed
  • Run npm install in the generated directory
  • Check for TypeScript compilation errors with npx tsc --noEmit
  • Verify the path in claude_desktop_config.json is absolute
  • Restart Claude Desktop after configuration changes
  • Check Claude Desktop logs for connection errors

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for detailed guidelines on:

  • Setting up the development environment
  • Code style and formatting requirements
  • Testing requirements
  • Pull request process

🐛 Reporting Issues

When reporting issues, please include:

  • Repository URL that caused the issue (if public)
  • Error messages or unexpected behavior
  • Node.js and pnpm versions
  • Operating system

📄 License

Apache 2.0. See LICENSE for details.

🔗 Links

Resource URL
📖 Documentation docs-github-to-mcp.vercel.app
🌐 Web App github-to-mcp.vercel.app
📦 npm Package npmjs.com/package/@nirholas/github-to-mcp
🔗 MCP Specification modelcontextprotocol.io
📘 MCP TypeScript SDK github.com/modelcontextprotocol/typescript-sdk
🐍 MCP Python SDK github.com/modelcontextprotocol/python-sdk
💬 Discussions github.com/nirholas/github-to-mcp/discussions

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trust, trustless, reputation, reputation system, reputation protocol, reputation registry, feedback, client feedback, user feedback, on-chain feedback, on-chain reputation, verifiable reputation, portable reputation, reputation aggregation, reputation scoring, reputation algorithm, trust signals, trust model, trust verification, trust layer, recursive reputation, reviewer reputation, spam prevention, Sybil attack, Sybil resistance, anti-spam, feedback filtering, trusted reviewers, rating, rating system, quality rating, starred rating, uptime rating, success rate, response time, performance history, track record, audit trail, immutable feedback, permanent feedback, feedback response, appendResponse, giveFeedback, revokeFeedback, feedback tags, feedback value, valueDecimals, feedbackURI, feedbackHash, clientAddress, reviewer address

Validation & Verification Keywords

validation, validation registry, validator, validator contract, cryptographic validation, cryptographic proof, cryptographic attestation, zero-knowledge, ZK, zkML, zero-knowledge machine learning, ZK proofs, trusted execution environment, TEE, TEE attestation, TEE oracle, stake-secured, staking validators, crypto-economic security, inference re-execution, output validation, work verification, third-party validation, independent validation, validation request, validation response, validationRequest, validationResponse, requestHash, responseHash, verifiable computation, verified agents, verified behavior, behavioral validation, agent verification

Payment & Commerce Keywords

x402, x402 protocol, x402 payments, programmable payments, micropayments, HTTP payments, pay-per-request, pay-per-task, agent payments, AI payments, agent monetization, AI monetization, agent commerce, AI commerce, agentic commerce, agent economy, AI economy, agent marketplace, service marketplace, agent-to-agent payments, A2A payments, stablecoin payments, USDC, crypto payments, on-chain payments, payment settlement, programmable settlement, proof of payment, proofOfPayment, payment receipt, payment verification, Coinbase, Coinbase x402, agent pricing, API pricing, service pricing, subscription, API keys, revenue, trading yield, cumulative revenues, agent wallet, payment address, toAddress, fromAddress, txHash

Discovery & Registry Keywords

agent discovery, service discovery, agent registry, identity registry, agent registration, register agent, mint agent, agent NFT, agent tokenId, agent browsing, agent explorer, agent scanner, 8004scan, 8004scan.io, agentscan, agentscan.info, 8004agents, 8004agents.ai, agent leaderboard, agent ranking, top agents, agent listing, agent directory, agent catalog, agent index, browse agents, search agents, find agents, discover agents, agent visibility, agent discoverability, no-code registration, agent creation, create agent, my agents, agent owner, agent operator, agent transfer, transferable agent, portable agent

Endpoints & Integration Keywords

endpoint, agent endpoint, service endpoint, API endpoint, MCP endpoint, A2A endpoint, web endpoint, HTTPS endpoint, HTTP endpoint, DID, decentralized identifier, ENS, Ethereum Name Service, ENS name, agent.eth, vitalik.eth, email endpoint, OASF, Open Agent Specification Format, endpoint verification, domain verification, endpoint ownership, .well-known, well-known, agent-registration.json, endpoint domain, endpoint URL, endpoint URI, base64 data URI, on-chain metadata, off-chain metadata, metadata storage, JSON metadata, agent JSON, registration JSON

SDK & Developer Tools Keywords

SDK, Agent0 SDK, Agent0, ChaosChain SDK, ChaosChain, Lucid Agents, Daydreams AI, create-8004-agent, npm, TypeScript SDK, Python SDK, JavaScript, Solidity, smart contract, ABI, contract ABI, deployed contracts, contract addresses, Hardhat, development tools, developer tools, dev tools, API, REST API, GraphQL, subgraph, The Graph, indexer, blockchain explorer, Etherscan, contract verification, open source, MIT license, CC0, public domain, GitHub, repository, code repository, documentation, docs, best practices, reference implementation

Ecosystem & Community Keywords

ecosystem, community, builder, builders, developer, developers, contributor, contributors, partner, partners, collaborator, collaborators, co-author, co-authors, MetaMask, Ethereum Foundation, Google, Coinbase, Consensys, AltLayer, Virtuals Protocol, Olas, EigenLayer, Phala, ElizaOS, Flashbots, Polygon, Base, Optimism, Arbitrum, Scroll, Linea, Monad, Gnosis, Celo, Near Protocol, Filecoin, Worldcoin, ThirdWeb, ENS, Collab.land, DappRadar, Giza Tech, Theoriq, OpenServ, Questflow, Semantic, Semiotic, Cambrian, Nevermined, Oasis, Towns Protocol, Warden Protocol, Terminal3, Pinata Cloud, Silence Labs, Rena Labs, Index Network, Trusta Network, Turf Network

Key People & Organizations Keywords

Marco De Rossi, MetaMask AI Lead, Davide Crapis, Ethereum Foundation AI, Head of AI, Jordan Ellis, Google engineer, Erik Reppel, Coinbase engineering, Head of Engineering, Sumeet Chougule, ChaosChain founder, YQ, AltLayer co-founder, Wee Kee, Virtuals contributor, Cyfrin audit, Nethermind audit, Ethereum Foundation Security Team, security audit, audited contracts

Use Cases & Applications Keywords

trading bot, DeFi agent, yield optimizer, data oracle, price feed, analytics agent, research agent, coding agent, development agent, automation agent, task agent, workflow agent, portfolio management, asset management, supply chain, service agent, API service, chatbot, AI assistant, virtual assistant, personal agent, enterprise agent, B2B agent, agent-as-a-service, AaaS, SaaS agent, AI SaaS, delegated agent, proxy agent, helper agent, worker agent, coordinator agent, orchestrator agent, validator agent, auditor agent, insurance agent, scoring agent, ranking agent

Technical Specifications Keywords

ERC-8004 specification, EIP specification, Ethereum Improvement Proposal, Ethereum Request for Comment, RFC 2119, RFC 8174, MUST, SHOULD, MAY, OPTIONAL, REQUIRED, interface, contract interface, function signature, event, emit event, indexed event, storage, contract storage, view function, external function, public function, uint256, int128, uint8, uint64, bytes32, string, address, array, struct, MetadataEntry, mapping, modifier, require, revert, transfer, approve, operator, owner, tokenId, URI, hash, keccak256, KECCAK-256, signature, deadline

Events & Conferences Keywords

8004 Launch Day, Agentic Brunch, Builder Nights Denver, Trustless Agent Day, Devconnect, ETHDenver, community call, meetup, hackathon, workshop, conference, summit, builder program, grants, bounties, ecosystem fund

News & Media Keywords

announcement, launch, mainnet launch, testnet launch, protocol update, upgrade, security review, audit, milestone, breaking news, ecosystem news, agent news, AI news, blockchain news, Web3 news, crypto news, DeFi news, newsletter, blog, article, press release, media coverage

Competitor & Alternative Keywords

agent framework, agent platform, AI platform, centralized agents, closed agents, proprietary agents, gatekeeper, intermediary, platform lock-in, vendor lock-in, data silos, walled garden, open alternative, decentralized alternativ