About MCP Agent Server
MCP Agent Server is an open-source platform for building and managing persistent AI agents, aimed at teams using n8n or other workflow engines. It combines natural-language task intake with agent-specific memory and feedback endpoints, and is designed for Docker deployment and extension through connectors and skills.
Key features
- 01Natural-language task intake
- 02Persistent, agent-specific memory
- 03Feedback and learning loops
- 04n8n and workflow-engine orchestration
- 05Docker Compose deployment
- 06Pluggable connectors and skills
Use cases
- 01Route natural-language requests into workflow tasks
- 02Keep agent memories and feedback between actions
- 03Build role-specific AI agents such as analysts or admins
MCP support
It provides an MCP server endpoint at http://localhost:4000. Its API includes agent memory, feedback, and trigger endpoints; the trigger endpoint is described as a stub for n8n integration.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
http://localhost:4000claude mcp add --transport http agent-server-leadbroaf http://localhost:4000{"mcpServers":{"agent-server-leadbroaf":{"type":"http","url":"http://localhost:4000"}}}Open in Cursor{"servers":{"agent-server-leadbroaf":{"type":"http","url":"http://localhost:4000"}}}Open in VS Code{"mcpServers":{"agent-server-leadbroaf":{"type":"http","url":"http://localhost:4000"}}}{"mcpServers":{"agent-server-leadbroaf":{"serverUrl":"http://localhost:4000"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEMCP Agent Server
This is the open-source "brain" for AI employees, designed to work with n8n and other workflow engines.
Quick Start
-
Clone the repo: git clone https://github.com/yourusername/mcp-agent-server.git cd mcp-agent-server
-
Copy over your docs and memory folders if needed.
-
Build and run with Docker Compose: docker-compose up --build
-
The MCP server will be available at http://localhost:4000
Getting Started
- Ensure you have Node.js and Docker installed.
- Remove any comments from package.json (JSON does not support comments).
- Run
npm installto install dependencies. - Use
docker-compose up --buildto start all services. - The server will be available at http://localhost:4000.
- For architecture and design, see the /docs and /memory folders and the "mcp-agent-server project plan" in MCP memory.
Project Structure
- /docs — Design, architecture, and usage documentation
- /memory — Persistent memory, logs, and knowledge
Project Vision: MCP Agent Server
The mcp-agent-server is an open-source, modular "brain" for AI employees/agents, designed to work seamlessly with n8n and other workflow engines.
-
AI Employee Metaphor:
Enables users to "hire," "assign," "grade," and "improve" persistent AI agents, each with their own memory, learning, and feedback loop. -
Opinionated & Agent-Centric:
Unlike generic workflow automation tools, the MCP agent server is opinionated and focused on the "AI employee" metaphor, making memory, feedback, and learning core features—not optional add-ons. -
Natural Language Interface:
Accepts natural language instructions (not just API calls or workflow triggers), parses them into actionable tasks, and orchestrates execution via n8n or other connectors. -
Proactive, Adaptive, and Personalized:
Agents can suggest actions, learn from user feedback, and improve over time. -
Vertical Solutions & Simplicity:
Supports vertical solutions (e.g., "AI Analyst," "AI Admin") with prebuilt skills, workflows, and feedback loops, as well as a simple, non-technical user experience for SMBs and individuals. -
Persistent, Agent-Centric Memory:
Memory and feedback are persistent and agent-centric, enabling agents to remember past actions, user preferences, and performance history. -
Easy Deployment & Extensibility:
Designed for easy deployment (Docker, Docker Compose), extensibility (pluggable connectors and skills), and SaaS monetization (multi-tenant, API key management, billing integration). -
Not Just Another Workflow Tool:
The MCP agent server is a platform for building, managing, and improving AI employees that work alongside humans, learn from experience, and deliver real business value.
For full design, architecture, and context, see the "mcp-agent-server project plan" entity in MCP memory and the /docs and /memory folders.
API Authentication
All endpoints (except /health, /users/register, and /users/login) require an x-api-key header. API keys are managed per user. See below for user and API key management.
User & API Key Management
Endpoints
POST /users/register— Register a new user (email, password)POST /users/login— Login and receive an API keyGET /users/me/api-keys— List your API keysPOST /users/me/api-keys— Create a new API keyDELETE /users/me/api-keys/:id— Revoke an API key
Example PowerShell Usage
# Register a new user
Invoke-RestMethod -Uri "http://localhost:4000/users/register" -Method Post -ContentType "application/json" -Body '{"email": "[email protected]", "password": "yourpassword"}'
# Login and get API key
$login = Invoke-RestMethod -Uri "http://localhost:4000/users/login" -Method Post -ContentType "application/json" -Body '{"email": "[email protected]", "password": "yourpassword"}'
$apiKey = $login.apiKey
# List API keys
Invoke-RestMethod -Uri "http://localhost:4000/users/me/api-keys" -Method Get -Headers @{ "x-api-key" = $apiKey }
# Create a new API key
Invoke-RestMethod -Uri "http://localhost:4000/users/me/api-keys" -Method Post -Headers @{ "x-api-key" = $apiKey }
# Revoke an API key (replace 1 with the actual key id)
Invoke-RestMethod -Uri "http://localhost:4000/users/me/api-keys/1" -Method Delete -Headers @{ "x-api-key" = $apiKey }
Example curl Usage
# Register a new user
curl -X POST http://localhost:4000/users/register -H "Content-Type: application/json" -d '{"email": "[email protected]", "password": "yourpassword"}'
# Login and get API key
curl -X POST http://localhost:4000/users/login -H "Content-Type: application/json" -d '{"email": "[email protected]", "password": "yourpassword"}'
# List API keys
curl http://localhost:4000/users/me/api-keys -H "x-api-key: <your-api-key>"
# Create a new API key
curl -X POST http://localhost:4000/users/me/api-keys -H "x-api-key: <your-api-key>"
# Revoke an API key (replace 1 with the actual key id)
curl -X DELETE http://localhost:4000/users/me/api-keys/1 -H "x-api-key: <your-api-key>"
Agent Memory & Feedback Endpoints
POST /agents/:id/memory— Add memory/feedback for an agent.GET /agents/:id/memory— List all memory/feedback for an agent.POST /agents/:id/trigger— Trigger an agent action (stub for n8n integration).
Example PowerShell Usage
$headers = @{ "x-api-key" = "changeme" }
# Create an agent
Invoke-RestMethod -Uri "http://localhost:4000/agents" -Method Post -Headers $headers -ContentType "application/json" -Body '{"name": "Test Agent"}'
# Add memory/feedback
Invoke-RestMethod -Uri "http://localhost:4000/agents/1/memory" -Method Post -Headers $headers -ContentType "application/json" -Body '{"content": "Agent completed onboarding."}'
# List memory/feedback
Invoke-RestMethod -Uri "http://localhost:4000/agents/1/memory" -Method Get -Headers $headers
# Trigger agent
Invoke-RestMethod -Uri "http://localhost:4000/agents/1/trigger" -Method Post -Headers $headers
Example curl Usage
curl -X POST http://localhost:4000/agents/1/memory -H "Content-Type: application/json" -H "x-api-key: changeme" -d '{"content": "Agent completed onboarding."}'
curl http://localhost:4000/agents/1/memory -H "x-api-key: changeme"
curl -X POST http://localhost:4000/agents/1/trigger -H "x-api-key: changeme"
Database Migrations & Schema Management
- All database migrations are applied automatically on container startup (see
docker-entrypoint.sh). - To add new models or fields:
- Edit
prisma/schema.prisma. - Run
npx prisma migrate dev --name <desc>locally (with your Docker Postgres running). - Commit the generated migration files in
prisma/migrations/to git.
- Edit
- On every deploy or container rebuild, all migrations will be applied automatically.
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