Adaptive Recall

io.github.AIAppsAPIPublished by GitHub account AIAppsAPIv1.0.1Updated Oct 24, 2026

Adaptive memory system with cognitive scoring, knowledge graph, and self-improving ML.

VerifiedSTDIODesktop onlyKnowledge & Memory AI & ML

Server details

Identifier: io.github.AIAppsAPI/adaptive-recall
Transport: STDIO
Runtime: Desktop only
Trust: Verified
Published: Sep 16, 2026

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Overview

AI-generated overview

Hosted long-term memory server that lets an assistant store, recall, update and forget memories with cognitive scoring and a knowledge graph.

What you can do: Store, update and forget memories, with automatic embeddings and entity extraction
Recall memories through multi-strategy retrieval ranked by cognitive scoring
Explore the knowledge graph by entity name and traversal depth
Inspect system status, memory counts, confidence distribution and knowledge gaps
Get a formatted snapshot of stored memories by type, and send developer feedback
When to use it: Useful when an assistant should keep durable long-term memory across sessions — user preferences, facts, project notes or procedures — and retrieve them with relevance ranking rather than plain keyword search.
Requirements: A hosted Adaptive Recall account: sign up to obtain a server URL and API key. The API key is supplied through the ADAPTIVE_RECALL_API_KEY environment variable or as a Bearer token in the Authorization header. Network access to the hosted endpoint is required; a paid plan may be needed beyond the free tier.

Before you install

All memories are sent to and stored on a third-party hosted service, so avoid storing secrets or sensitive personal data. The API key is a credential and should be kept out of shared configs. Forget removes memories, and update overwrites existing content. Plans beyond the free tier are paid.

Installation

In SourceWeft

Open Adaptive Recall in the dashboard and add it to a workspace.
Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

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.

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

Connect

MCP Configuration

Add to your MCP client config (Claude Code, Codex, Cursor, or any MCP-compatible tool):

json

{  "mcpServers": {    "adaptive-recall": {      "type": "url",      "url": "https://YOUR_SERVER_URL/mcp",      "headers": {        "Authorization": "Bearer YOUR_API_KEY"      }    }  }}

{  "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

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.

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

Source: README.md at commit 60e898c

Tools

SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

v1.0.1LatestSep 16, 2026

Score

50% of the applicable checks met

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Reached in the last 30 days25 pts
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Auth declared10 pts
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Tools listed15 pts
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DescriptionRequired15 pts
Logo10 pts
Documentation15 pts
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