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Agent Recall

Local, correction-first agent memory with session controls, retrieval, alignment checks, and behavior measurement.

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Install Agent Recall

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "agent-recall": {
      "command": "npx",
      "args": [
        "-y",
        "agent-recall-mcp"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Automated check passed— started and listed 5 tools correctly (1mo ago).

Overview

Correction-first project memory is provided by the agent-recall MCP server, which stores structured facts, decisions, and human corrections across sessions. Its five MCP tools cover session loading and saving, explicit memory writes, retrieval, and pre-action alignment checks. Memory is local-only by default, making it suitable for projects that need persistent context without a hosted memory service. Reach for it when an agent must carry decisions between sessions and record whether corrections are later followed.

Use cases

  • Load project decisions before starting a new agent session
  • Record human corrections as durable structured memory
  • Search prior context when resuming project work
  • Check planned deployments or external sends against stored rules
  • Measure whether later sessions heed recorded corrections

Key features

  • Local project memory across sessions
  • Structured corrections ledger
  • Session start and explicit save lifecycle
  • Keyword and RRF retrieval
  • Pre-action alignment checks with blocking verdicts
  • Correction outcome measurement

Tools5

What Agent Recall lets your agent do. Expand a tool for its parameters.

Verified live~2.4k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

18/18 checks healthy over the last 92d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 6d ago via OSV.dev · agent-recall-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars375Stargazers on the source repository.
npm downloads1kPackage downloads in the last 30 days.
Last commit2d agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed5Callable tools this server registers over MCP.
Directory activity9 viewsConfig copies, upvotes, and views on AllMCPs.

How Agent Recall works

What agent-recall MCP server does

The agent-recall MCP server gives an MCP client a local memory workflow for project sessions. It is designed around a corrections ledger: human corrections can be recorded as structured entries rather than left only in conversation history. Stored information can include facts, decisions, insights, and rules that should affect later work.

The system also tracks correction outcomes. Retrieved corrections accumulate a retrieval count, while later encounters can be marked as either heeded or recurred. This makes behavioral follow-through measurable instead of treating successful retrieval as proof that an agent changed its behavior.

As a 🧠 Knowledge & Memory tool, agent-recall fits work where decisions and correction history need to persist across agent restarts, sessions, and projects. The repository reports local storage and zero cloud use by default.

How it works

A session normally begins with session_start, which loads project context before the agent acts. The lite mode returns a shorter briefing of up to 500 tokens for conversations where the agent will retrieve more detail on demand. During work, recall searches prior memory, while remember writes one fact, decision, or insight when the user explicitly asks for it.

Before a risky or irreversible action, check can compare the planned action with stored corrections, rules, and insights. It returns a verdict; blocked means an authoritative correction overrides the plan. A durable correction should be supplied as the structured object {rule, why, applies_when}. A plain-text correction is staged for later review rather than activated immediately.

session_end is the explicit save or exit operation. Nothing is saved automatically through that lifecycle call, and the tool can also update the project’s phase narrative with close_phase and open_phase.

Setup and configuration

The agent-recall MCP server can be launched through npm with npx -y agent-recall-mcp. Claude Code users can add it with:

Terminal
claude mcp add --scope user agent-recall -- npx -y agent-recall-mcp

Other stdio-capable MCP clients can use an entry with command set to npx and arguments -y, agent-recall-mcp.

Tools and capabilities

  • session_start: load project memory at the beginning of a session.
  • session_end: save session context and optionally update project phases.
  • remember: write a specific fact, decision, insight, or correction.
  • recall: retrieve previous memory, context, or decisions.
  • check: validate alignment and inspect stored constraints before an action.

Limitations and notes

The agent-recall MCP server depends on explicit tool use. Agents must call session_start before acting and session_end when saving or exiting; the material states that nothing is saved automatically. Saying a fact in conversation is not equivalent to writing it with remember.

The published measurements also show that the system should not be treated as proof that corrections will always be captured or followed. The supplied results report 35.3% correction-capture recall in one audit, zero of three evidence-grounded heed events after a measurement reset, and zero of four correction-transfer events in an offline benchmark. These figures describe the project’s reported corpus and evaluation state, not a guarantee for another workload.

The repository’s setup examples use a local stdio process.

Read the full README View source on GitHub

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Frequently Asked Questions about Agent Recall

agent-recall is an MCP server that connects an MCP client to local project memory and a corrections ledger. Its main tools are session_start, session_end, remember, recall, and check, covering session lifecycle, explicit memory writes, retrieval, and alignment checks before risky actions. It stores memory locally by default.

Install it by registering the stdio command `npx -y agent-recall-mcp` with your MCP client. Claude Code can use `claude mcp add --scope user agent-recall -- npx -y agent-recall-mcp`; the README also provides JSON examples for Cursor, VS Code, Windsurf, and Codex.

Call `remember` for one fact, decision, insight, or correction, and call `session_end` when saving or exiting a session. The documented workflow does not auto-save, so stating something in the conversation does not write it to persistent memory.

Yes. Call `check` with an `action_description` before a publish, deploy, delete, credential exposure, external message, or other irreversible write. If the returned verdict is `blocked`, an authoritative stored correction overrides the plan and should be read before proceeding.

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