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altk-evolve

by AgentToolkit·84·Score 46

Evolve provides AI agents with memory and learning capabilities through MCP server integration.

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Overview

Evolve is a system that helps AI agents improve over time by learning from their interactions and experiences. It uses an MCP server for tool integration, vector storage for memory management, and LLM-based conflict resolution to refine its knowledge base. The system maintains a feedback loop, taking conversation traces from agents, extracting key insights into a database, and feeding that information back to improve future performance. It supports both lite mode for existing agent assistants and a full MCP server implementation with comprehensive entity management capabilities.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

you:Enhance coding assistants with learning capabilities from past interactions
you:Create knowledge-sharing systems for AI agents across teams
you:Improve reliability of AI agents on complex multi-step tasks
you:What is the difference between Lite mode and full MCP server mode?
you:How does Evolve handle conflicting guidelines?

When to choose this

Choose Evolve when you need AI agents that learn and improve from past interactions, particularly for coding or complex multi-step tasks where agents would otherwise repeat the same mistakes.

When NOT to choose this

Avoid Evolve if you need a simple, lightweight solution without persistent memory or if you're not using Python-based agents, as it requires Python 3.12+ and has multiple dependencies.

Tools this server exposes

7 tools extracted from the README
  • get_entitiesget_entities(task: str, entity_type: str = "guideline", include_public: bool = False)

    Get relevant entities for a specific task

  • get_guidelinesget_guidelines(task: str)

    Get relevant guidelines for a specific task

  • save_trajectorysave_trajectory(trajectory_data: str, task_id: str | None, owner_id: str | None)

    Save a conversation trajectory and generate new guidelines

  • create_entitycreate_entity(content: str, entity_type: str, metadata: str | None, enable_conflict_resolution: bool, owner_id: str | None, visibility: str = "private")

    Create a new entity with optional conflict resolution

  • publish_entitypublish_entity(entity_id: str, user_id: str | None)

    Make an entity publicly visible to all namespaces

  • unpublish_entityunpublish_entity(entity_id: str, user_id: str | None = None)

    Revert an entity to private visibility

  • delete_entitydelete_entity(entity_id: str)

    Delete a specific entity by its ID

Comparable tools

memgptgpt-researchersemantic-workspacecognitive_architectautogen

Installation

Installation

Prerequisites:

  • Python 3.12 or higher
  • uv (recommended) or pip

From Source:

git clone https://github.com/agenttoolkit/altk-evolve.git
cd altk-evolve
uv venv --python=3.12 && source .venv/bin/activate
uv sync
# Build the UI
cd frontend/ui
npm ci && npm run build
cd ../..

From PyPI:

pip install altk-evolve

Configuration

For direct OpenAI usage:

export OPENAI_API_KEY=sk-...

Running Services

Start the Web UI and MCP server:

uv run evolve-mcp

The Web UI can be accessed from: http://127.0.0.1:8000/ui/

Claude Desktop Integration

Add to Claude Desktop configuration:

{
  "mcpServers": {
    "evolve": {
      "command": "uv",
      "args": ["run", "evolve-mcp"]
    }
  }
}

FAQ

What is the difference between Lite mode and full MCP server mode?
Lite mode is designed to integrate with existing agent assistants like Claude Code and Codex without the full Interaction layer. Full MCP server mode includes all features including comprehensive entity management, conflict resolution, and sharing capabilities through the MCP protocol.
How does Evolve handle conflicting guidelines?
Evolve uses LLM-based conflict resolution to refine its knowledge base. When new information contradicts existing guidelines, it automatically updates them based on the new insights, improving the knowledge base over time.

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Last updated · Auto-generated from public README + GitHub signals.