Adaptive Recall
A hosted memory layer that stores and retrieves context for AI applications using four parallel search strategies: vector similarity, temporal recency, keyword matching, and knowledge graph traversal. It automatically extracts entities and relationships from stored memories, ranks results using cognitive science activation models, and trains ML models on your usage patterns to improve retrieval quality over time. Memories have lifecycle stages and gain or lose confidence based on corroboration. You get eight actions including store, recall, update, forget, and graph traversal. Connect via MCP or REST API with your server URL and API key. Useful when you need persistent memory across sessions that actually learns which retrieval strategy works best for different query types rather than just doing basic vector search.
- GitHub stars
- 3
- tools
- 8
- auth
- Secret needed
- transport
- HTTP
- env var
- 1
- last updated
- May 13, 2026
Tools
8 toolsPublic tool metadata for what this MCP can expose to an agent.
storeSave a new memory. Generates embeddings and extracts entities automatically.
Save a new memory. Generates embeddings and extracts entities automatically.
No parameter schema in public metadata yet.
recallSearch memories using multi-strategy retrieval with cognitive scoring.
Search memories using multi-strategy retrieval with cognitive scoring.
No parameter schema in public metadata yet.
updateModify an existing memory. Re-embeds automatically if content changes.
Modify an existing memory. Re-embeds automatically if content changes.
No parameter schema in public metadata yet.
forgetRemove a memory by ID or by finding the closest match to a query.
Remove a memory by ID or by finding the closest match to a query.
No parameter schema in public metadata yet.
graphExplore the knowledge graph, traversing entity relationships by name and depth.
Explore the knowledge graph, traversing entity relationships by name and depth.
No parameter schema in public metadata yet.
statusSystem health, memory counts, confidence distribution, and knowledge gap detection.
System health, memory counts, confidence distribution, and knowledge gap detection.
No parameter schema in public metadata yet.
snapshotGet a formatted overview of stored memories, organized by type.
Get a formatted overview of stored memories, organized by type.
No parameter schema in public metadata yet.
feedbackSend feedback directly to the Adaptive Recall developers.
Send feedback directly to the Adaptive Recall developers.
No parameter schema in public metadata yet.
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ADAPTIVE_RECALL_API_KEY*secretYour Adaptive Recall API key (get one free at adaptiverecall.com)
Readme
Adaptive Recall
Adaptive memory system for AI applications. Patent pending.
adaptiverecall.com | Documentation | Sign Up Free
What It Does
Adaptive Recall is a hosted memory server that stores, retrieves, and manages long-term memory for AI applications. It connects via MCP or REST API.
Details
- Repository
- github.com/aiappsapi/adaptive-recall
- Categories
- AI & LLM Tools, Documents & Knowledge
- Package
adaptive-recall- Transport
- HTTP
- Auth
- Required
- Registry
- MCP registry, active
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