adaptive-agent-mcp 0.5.3

Self-Evolving RAG for AI Agents — A cross-app persistent memory system where agents autonomously write, retrieve, and evolve their knowledge

Self-Evolving RAG for AI Agents

Agents don't just read memory — they write it.

中文 | English

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Core Concept

Traditional RAG User Input → Retrieve KB → Generate ↑ Read-only (Human-maintained)

Self-Evolving RAG User Input → Retrieve Memory → Generate ↑↓ Read + Write Agent autonomously evolves

Key Differences:

	Traditional RAG	Adaptive Agent MCP
Read	Retrieves pre-indexed documents	Dynamically accumulates at runtime
Write	Human-maintained knowledge base	Agent writes autonomously
Scope	Generic knowledge	User-specific memory
State	Static data	Continuously evolves

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How It Works

In Claude Code: "Remember, I prefer TypeScript"
         ↓
    Agent automatically calls:
    • append_daily_log() → Record to daily log
    • update_preference() → Update preferences
    • extract_knowledge() → Extract knowledge graph
         ↓
In Antigravity: "What are my coding preferences?"
         ↓
    AI: "You prefer TypeScript"

Teach once, remember forever. Share across apps, never forget.

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Quick Start

Installation

Configure mcp.json in any MCP-compatible AI application:

Basic Configuration:

{
  "mcpServers": {
    "adaptive-agent-mcp": {
      "command": "uvx",
      "args": ["adaptive-agent-mcp"]
    }
  }
}

Full Configuration (with Semantic Search API):

{
  "mcpServers": {
    "adaptive-agent-mcp": {
      "command": "uvx",
      "args": ["adaptive-agent-mcp"],
      "env": {
        "ADAPTIVE_EMBEDDING_BASE_URL": "https://api.openai.com/v1",
        "ADAPTIVE_EMBEDDING_API_KEY": "your-api-key",
        "ADAPTIVE_EMBEDDING_MODEL": "text-embedding-3-small",
        "ADAPTIVE_RERANK_BASE_URL": "https://api.cohere.ai/v1",
        "ADAPTIVE_RERANK_API_KEY": "your-api-key",
        "ADAPTIVE_RERANK_MODEL": "rerank-english-v3.0"
      }
    }
  }
}

Default storage path: ~/.adaptive-agent/memory. All apps share the same memory.

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Features

Feature	Description	Version
Three-Layer Memory	MEMORY.md + Daily Logs + Knowledge Graph	v0.1.0
Scope Isolation	project:xxx, app:xxx, global	v0.2.0
Concurrent Safety	Cross-process file locking	v0.3.0
Incremental Indexing	mtime-based smart updates	v0.3.0
Semantic Search	Embedding + Rerank API	v0.4.0
FTS5 Full-text	SQLite built-in search	v0.4.0
Knowledge Graph	NetworkX-based entity relations	v0.5.0

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Available Tools

Memory Management

Tool	Description
initialize_session	Initialize session with user profile and recent context
append_daily_log	Append content to today's log
update_preference	Intelligently update user preferences
query_memory_headers	Query memory file metadata
read_memory_content	Read complete memory file content
search_memory_content	Full-text search using ripgrep

Semantic Search

Tool	Description
semantic_search	Vector similarity search
fulltext_search	FTS5 keyword search with BM25 ranking
index_document	Index document to vector store

Knowledge Graph

Tool	Description
extract_knowledge	Extract entity relations from text
add_knowledge_relation	Manually add relations
query_knowledge_graph	Query entities, relations, or stats
multi_hop_query	Multi-hop reasoning queries

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Storage Structure

~/.adaptive-agent/memory/
├── MEMORY.md              # User preferences (scope-based)
├── .knowledge/
│   └── items.json         # Atomic facts
├── .vector/
│   └── vector.db          # SQLite + sqlite-vec
├── .graph/
│   └── knowledge.json     # NetworkX graph
└── 2026/
    └── 02_february/
        └── week_06/
            └── 2026-02-07.md  # Daily logs

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Data Safety

• Isolated storage: Data stored in ~/.adaptive-agent/memory, independent of uvx installation
• Concurrent safety: filelock prevents data corruption from multiple clients
• Human-readable: All data in Markdown/JSON format, easy to backup and version control

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Documentation

• Architecture Design (Chinese)
• Local Model Setup
• Changelog

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License

MIT License - See LICENSE for details.

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Adaptive Agent MCP — Where agents learn, remember, and evolve.