summon-mcp
by Aiskillhub
README.md
# Summon
Self-evolving knowledge graph for AI agents — persistent memory that gets smarter with every interaction.
**pip install, 2 lines of config, your agent remembers everything.**
[](https://pypi.org/project/summon-mcp/)
[](LICENSE)
[](https://www.python.org/)
## Why Summon?
AI agents forget everything between sessions. Vector DBs remember but don't understand relationships. Summon gives agents **structured, evolving memory** that:
- **Self-evolves** — frequently used knowledge strengthens; stale knowledge decays
- **Connects the dots** — automatic relationship detection between memories (graph edges)
- **Detects contradictions** — flags conflicting memories before they poison your agent's output
- **Learns from usage** — recall feedback loop tunes retention automatically
## Quick Start
### Install
```bash
pip install summon-mcp
```
### Use as a Python SDK
```python
from summon import Summon
sb = Summon()
# Remember
sb.remember("The production database is PostgreSQL 15 on AWS RDS", tags=["db", "prod"])
sb.remember("API rate limit is 1000 req/min per user", tags=["api", "limits"])
# Recall
results = sb.recall("what database do we use?")
for r in results:
print(f"[{r.confidence:.0%}] {r.content}")
# Link memories
sb.link(source_id=1, target_id=2, relationship="depends_on")
# Traverse the knowledge graph
graph = sb.traverse(memory_id=1, hops=2)
```
### Use with Claude Code
Add to `~/.claude/claude_desktop_config.json`:
```json
{
"mcpServers": {
"summon": {
"command": "python",
"args": ["-m", "summon"],
"env": {
"SUPERBRAIN_DB_PATH": "~/.summon/memory.db"
}
}
}
}
```
That's it. Claude Code now has persistent memory.
## Features
### 30 MCP Tools
| Category | Tools |
|----------|-------|
| **Memory CRUD** | `remember`, `recall`, `forget`, `reinforce` |
| **Knowledge Graph** | `link`, `traverse`, `find_similar`, `associative_recall` |
| **Evolution** | `decay_maintenance`, `auto_tune`, `dream`, `evolve` |
| **Analysis** | `detect_contradictions`, `synthesize`, `compress`, `clusters` |
| **Export** | `export_cards`, `export_knowledge`, `export_vectors`, `mermaid` |
| **Meta** | `health`, `status`, `changelog`, `diff`, `weekly_report` |
### Self-Evolution Engine
- **Edge heating** — frequently traversed paths strengthen; cold ones decay
- **SM-2 spaced repetition** — memories reviewed on optimal schedules (like Anki)
- **Auto-tune decay** — retention thresholds adjust based on actual usage patterns
- **Recall feedback loop** — tracks which searches were useful, learns from it
- **Episodic consolidation** — old episodes auto-summarize into permanent facts
### Storage
- **SQLite** — zero-config local storage, perfect for single-user
- **Pluggable backends** — swap in PostgreSQL, ChromaDB, or custom stores
- **BYOM embeddings** — bring your own model (OpenAI, DeepSeek, Ollama, local sentence-transformers)
## SDK Reference
```python
from summon import Summon, Memory, Edge
sb = Summon() # local SQLite (default)
sb = Summon(base_url="...", api_key="...") # remote API
# Write
mem = sb.remember("fact", tags=["tag"], confidence=0.8)
# Read
mem = sb.get(memory_id)
results = sb.recall("query", mode="hybrid", limit=10)
# Graph
edge_id = sb.link(source=1, target=2, relationship="depends_on")
graph = sb.traverse(memory_id=1, hops=2)
# Manage
sb.reinforce(memory_id)
sb.forget(memory_id, mode="decay") # or mode="delete"
sb.stats() # database statistics
sb.strongest() # top memories
sb.weakest() # at-risk memories
```
## Community
- **License**: Apache 2.0 — free for commercial use
- **Python**: 3.9+
- **Status**: v0.4.0 Beta — stable for personal use, API may evolve before 1.0
## Roadmap
- [ ] Cloud sync ($5/mo)
- [ ] Multi-tenant SaaS
- [ ] LangChain / CrewAI integrations
- [ ] Web dashboard
- [ ] v1.0 stable API
---
Built for developers who want their AI agents to stop forgetting.
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