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.
Adaptive memory system for AI applications. Patent pending.
adaptiverecall.com | Documentation | Sign Up Free
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.
Sign up at adaptiverecall.com to get your server URL and API key.
Add to your MCP client config (Claude Code, Codex, Cursor, or any MCP-compatible tool):
{
"mcpServers": {
"adaptive-recall": {
"type": "url",
"url": "https://YOUR_SERVER_URL/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}
For Claude Code, add this to .mcp.json in your project or ~/.claude/settings.json for global access. For Gemini CLI, add to ~/.gemini/settings.json using httpUrl instead of url. For Codex, add to your Codex MCP configuration.
Every action is also available as an HTTP endpoint at https://YOUR_SERVER_URL/v1/. All requests require a Bearer token in the Authorization header.
| Action | Description |
|---|---|
| store | Save a new memory. Generates embeddings and extracts entities automatically. |
| recall | Search memories using multi-strategy retrieval with cognitive scoring. |
| update | Modify an existing memory. Re-embeds automatically if content changes. |
| forget | Remove a memory by ID or by finding the closest match to a query. |
| graph | Explore the knowledge graph, traversing entity relationships by name and depth. |
| status | System health, memory counts, confidence distribution, and knowledge gap detection. |
| snapshot | Get a formatted overview of stored memories, organized by type. |
| feedback | Send feedback directly to the Adaptive Recall developers. |
When storing memories, assign a type that affects how the memory is managed:
Learning types (evolve over time, gain/lose confidence, have lifecycle stages):
general_knowledge - facts, observations, reference informationuser_knowledge - information about people and their preferencesLookup types (static reference, no lifecycle):
callable_scripts - tool and script referenceswork_project - project tracking, tasks, deadlinescross_reference - pointers to external information and resourceslearned_procedure - multi-step workflows and proceduresFree, Starter, Pro, and Business plans available. See adaptiverecall.com for details.
ADAPTIVE_RECALL_API_KEY*secretYour Adaptive Recall API key (get one free at adaptiverecall.com)
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