Fetch Agents

by SoftwareValete

292 downloads

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GitHub

About

AI-powered code analysis and context optimization tools. Slim large code files to relevant sections (save 60-80% tokens), compress text, analyze conversations for noise, and search past chat knowledge bases. Supports x402 micropayments on Base.

Details

Author: SoftwareValete
Downloads: 292
Categories: Automation, Knowledge Base, Developer Tools

- Reduce code files to only relevant sections with slim_code
- List and extract LAYER sections from code files
- Compress long text while preserving key information
- Analyze conversations for noise and wasted tokens
- Index chat exports into a searchable knowledge base
- Search indexed knowledge bases for past discussion insights
- Pay-per-use via x402 micropayments on Base

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Fetch Agents

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

From the repository

Obtain a free API key by registering via curl (50 free requests/day included). Add the server to your MCP config with the python command, the script mcp_server.py, and the API key in environment variables. Install dependencies with pip install mcp httpx. Optionally use x402 micropayments to pay per request without registration.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "fetch agents": {
            "fetch-agents": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "cwd": "/path/to/fetch-agents-mcp"
            }
        }
    }
}

McpServers

{
    "fetch-agents": {
        "command": "python",
        "args": [
            "mcp_server.py"
        ],
        "cwd": "/path/to/fetch-agents-mcp"
    }
}

Fetch Agents MCP Server

MCP server providing AI-powered code analysis, context compression, and knowledge search tools for Claude Code, Cline, and other MCP-compatible AI assistants.

Tools

| Tool | Description | Use When |
|------|-------------|----------|
| slim_code | Reduce a code file to only sections relevant to your task | Reading large files, saving tokens |
| map_layers | List all LAYER sections in a code file | Exploring unfamiliar code structure |
| extract_layer | Extract one specific named LAYER section | Focused reading of a single component |
| compress_text | Compress long text while preserving key information | Summarizing docs, logs, verbose output |
| analyze_context | Find noise and wasted tokens in conversations | Long conversations hitting context limits |
| teleport_chat | Index a chat export into searchable knowledge base | Reusing insights from past conversations |
| search_knowledge | Search indexed knowledge bases | Finding relevant past discussions |

Quick Start

1. Get a free API key

curl -X POST https://agentslab.duckdns.org/code/register \
  -H "Content-Type: application/json" \
  -d '{"name": "my-project"}'

50 free requests/day included.

2. Add to your MCP config

Claude Code (~/.claude/.mcp.json):

{

  "mcpServers": {

    "fetch-agents": {

      "command": "python",

      "args": ["mcp_server.py"],

      "cwd": "/path/to/fetch-agents-mcp",

      "env": {

        "FETCH_API_KEY": "fak_your_key_here"

      }

    }

  }

}

Cline (VS Code settings):

{

  "cline.mcpServers": {

    "fetch-agents": {

      "command": "python",

      "args": ["mcp_server.py"],

      "cwd": "/path/to/fetch-agents-mcp",

      "env": {

        "FETCH_API_KEY": "fak_your_key_here"

      }

    }

  }

}

3. Install dependencies

pip install mcp httpx

x402 Payments (No API Key Needed)

All endpoints support x402 micropayments on Base (Coinbase L2). Any AI agent with a USDC wallet can pay per-request without registration:

POST /code/slim -> 402 Payment Required + payment-required header
-> Agent signs USDC transfer -> retries with payment header -> gets response

Prices: $0.10 - $1.00 per request depending on tool.

How It Works

The MCP server connects to cloud-hosted agents at agentslab.duckdns.org via HTTPS. Your code is processed server-side using LLM-powered analysis pipelines. No local GPU needed.

Your IDE -> MCP Server -> HTTPS -> Cloud Agents -> Response

Example Usage

Once installed, your AI assistant can use the tools naturally:

> "Use slim_code to get only the authentication-related code from this file"

> "Compress this error log to the key information"

> "Search my teleported knowledge base for how we handled rate limiting"

Pricing

| Tier | Price | Included |
|------|-------|----------|
| Free | $0 | 50 requests/day |
| Pay-per-use (x402) | $0.10-1.00 | Per request, USDC on Base |
| Prepaid balance | Top up via crypto | BTC, ETH, USDC, + 10 more |
| Pro subscription | $15/mo | 300 requests/mo |

Requirements

- Python 3.10+
- mcp and httpx packages
- Internet connection (tools call cloud APIs)

License

MIT

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About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Fetch Agents MCP Server

Tools

Quick Start

1. Get a free API key

2. Add to your MCP config

3. Install dependencies

x402 Payments (No API Key Needed)

How It Works

Example Usage

Pricing

Requirements

License

Install

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