Adaptive Recall

Adaptive memory system for AI applications. Patent pending.

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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.

• Multi-strategy retrieval: four search strategies run in parallel (vector similarity, temporal recency, full-text keyword, knowledge graph traversal) and the system learns which to prioritize for each type of query

• Cognitive scoring: results ranked using ACT-R activation modeling from cognitive science, factoring in recency, access frequency, entity connections, and validated confidence

• Knowledge graph: entities and relationships extracted automatically from stored memories, used as a retrieval pathway alongside text similarity

• Memory lifecycle: memories progress through stages, gain or lose confidence based on corroborating evidence, and fade naturally when unused

• Self-improving: ML models train on your usage patterns, every parameter change must pass statistical validation against real query history before being adopted

• Retrieval quality monitoring: the system verifies its own retrieval consistency and identifies knowledge gaps

Related MCP server: r3 (Recall)

Connect

Sign up at adaptiverecall.com to get your server URL and API key.

MCP Configuration

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.

REST API

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.

Actions

Memory Types

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 information

• user_knowledge - information about people and their preferences

Lookup types (static reference, no lifecycle):

• callable_scripts - tool and script references

• work_project - project tracking, tasks, deadlines

• cross_reference - pointers to external information and resources

• learned_procedure - multi-step workflows and procedures

Pricing

Free, Starter, Pro, and Business plans available. See adaptiverecall.com for details.

Links

• Website

• Documentation

• Sign Up