adaptive-recall — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited adaptive-recall (Plugin) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.