Recallium

recallium-ai58stars

1# Recallium

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
License: NOASSERTION
Last checked: 2026-10-28

Stars: 58
Tools: —
Uptime: —

Overview

About Recallium

Engineering memory for coding agents: the decisions, fixes and constraints behind your code, with who recorded them, the files and the commit, recalled by every agent on the team in Claude Code, Codex, Cursor, Copilot and 60+ MCP clients. Self-hosted community edition; Recallium Cloud at recallium.ai.

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Recallium?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Recallium need an API key?

No required environment variable is listed on this record.

What transport does Recallium use?

Recallium runs locally over stdio.

When was Recallium last checked?

Last checked 2026-10-28. Engineering memory for coding agents: the decisions, fixes and constraints behind your code, with who recorded them, the files and the commit, recalled by every agent on the team in Claude Code, Codex, Cursor, Copilot and 60+ MCP clients. Self-hosted community edition; Recallium Cloud at recallium.ai.

From the publisher

Documentation

Recallium

Institutional engineering memory for humans and AI agents.

Your code remembers what changed. Recallium remembers why.

What Recallium is
Serving memory vs. engineering memory
How it works
Install
Use it from your coding agent
Projects and workstreams
Memory across the software lifecycle
Supported coding agents and IDEs
Where it helps
Rules files and Recallium
Retrieval
Privacy and data handling
Pricing
FAQ
Self-hosted community edition (formerly MiniMe MCP)
Migrating from the community edition to Recallium Cloud
Links
License

What Recallium is

Recallium is memory for the agents that do software development, such as Claude Code, Codex, Cursor, GitHub Copilot, Devin and Cline, and for the engineers who work beside them. It is served over the Model Context Protocol (MCP), so every coding tool on the team is a client of the same memory.

While an agent designs, decides, builds, debugs and ships, Recallium keeps the record it produces: the decision and the options rejected, the root cause and the fix, the constraint that drove a change, the rules the team follows, and where an effort stands. When a later session, another tool or a teammate's agent touches the same code, Recallium finds what the team already settled and feeds it to the agent before it starts. When one decision replaces another, agents follow the current one.

Teams also call this memory for development agents, developer agents, AI coding assistants or AI software engineering agents. All of those mean the agents that do the development work. Recallium is not a memory API for the end users of the product you ship; it is memory for the team that ships it.

Serving memory vs. engineering memory

Every AI memory pitch sounds the same: your agent never forgets, persistent context, memory for AI. Two different products are sold under one word. Serving memory remembers the person your product talks to. Engineering memory remembers why your software is the way it is.

Serving memory lives in your product's runtime. A support bot remembers a customer's last three orders; a tutoring app remembers a student struggles with fractions. The unit of memory is a person, the job is personalization, the scale is millions of end users, so the bill is metered by requests and tokens. Engineering memory lives in your team's build process. The unit is a decision: what was chosen, what was rejected, the constraint that forced it, and what replaced it later. The readers are the engineers and coding agents building the product, so it is priced per engineer.

	Serving memory	Engineering memory
Remembers	The person on the other side of the chat	Why the software is the way it is
Unit of memory	A fact about a user	A decision, a fix, a constraint, with its reasoning
Who reads it	Your product, on behalf of each end user	Every engineer and every coding agent on the team
What "current" means	The latest preference wins	The latest decision wins, and the old one stays on record
Scale	Millions of end users	One team, many repositories, many tools
Billed by	Requests, tokens, queries	Engineer
Cost of a stale memory	A slightly worse reply	A bug your security review already killed, shipped again

That last row is the whole argument. In serving memory a stale fact is an annoyance; in engineering memory a stale fact is an incident. A stale memory is more dangerous than a missing one, which is why Recallium keeps the old decision on record and makes the current one explicit.

Mem0, Supermemory and Zep are serving memory, and good at it; Mem0 and Supermemory also ship Claude Code and Cursor plugins that remember the developer as a user. Letta builds stateful agents whose memory belongs to the agent. None of them is memory for the team: one record read and written by Claude Code on one laptop, Codex on another and Cursor on a third, often in the same afternoon. That is the job Recallium is built for.

#engineering-memory #serving-memory #ai-memory #agent-memory #ai-agent-memory #memory-for-coding-agents #memory-for-development-agents #developer-agent-memory #ai-software-engineering-agents #sdlc-memory #institutional-memory #team-memory #mcp #mcp-server #mcp-memory-server #model-context-protocol #claude-code #claude-code-memory #codex #codex-memory #cursor #cursor-memory #github-copilot #copilot-memory #claude-desktop #windsurf #cline #devin #ai-coding-agent #ai-coding-assistant #coding-agents #persistent-memory #context-management #llm-context #cross-session-memory #cross-tool-memory #developer-productivity #self-hosted #developer-tools #minime-mcp

How it works

Engineering context that compounds: your team works, Recallium organizes the context by project, workstream and files, and future work resumes from what the team already knows

Your team works. People and agents design, implement, debug, test and review. Decisions and lessons form while the work is fresh.
Recallium preserves the context. The useful reasoning stays organized by project, workstream and the files it is about, scoped by project access.
Future work starts informed. Any connected agent retrieves the earlier decisions, warnings and next steps: why was this chosen, what did we try already, what should change next.

You work through normal conversation. Ask your agent to remember a decision, investigate earlier fixes, or leave a continuation point; the integration attaches the context to the right project. Search works by meaning as well as by exact terms and file paths, so you ask the question you need answered instead of remembering a document title.

Install

Recallium Cloud is the managed service. One command connects every coding agent on the machine. It needs Node.js 22 or later; nothing is installed first, every command runs through npx.

npx -y recallium@latest install

The Recallium installer: eleven agents found on this machine, eight wired to api.recallium.ai, with install and uninstall modes and a system check

The installer detects the installed agents, signs you in once, shows its plan and writes nothing until you confirm. In every client the MCP server is named recallium, and the project name is derived from the Git repository. Then open a repository in your coding agent and ask, for example: "What decisions and open tasks should I know about before I change the authentication flow?"

Command	Purpose
`npx -y recallium@latest install`	Detect coding agents, review the setup, connect them and sign in
`npx -y recallium@latest status`	Show client, sign-in, server and connected-agent state
`npx -y recallium@latest doctor`	Run capture-health and integration checks, with the repair for each failed one
`npx -y recallium@latest login`	Sign in again or replace a lost or revoked credential
`npx -y recallium@latest update`	Update when a newer client is available
`npx -y recallium@latest uninstall`	Open the Install / Modify screen and remove selected agents
`npx -y recallium@latest uninstall --all`	Remove all Recallium agent wiring and local Recallium state

Use --dry-run on install or uninstall to preview the affected files first. The installer and uninstaller preserve configuration entries they do not own.

Recallium Cloud is in a closed pilot. Join the waitlist at recallium.ai/waitlist; pilot code holders join at app.recallium.ai/pilot/join.

Read more: Quickstart · CLI reference · Install options · Remove Recallium · Prerequisites and troubleshooting · per-client setup for Claude Code, Codex, Cursor, GitHub Copilot, VS Code and Claude Desktop.

Use it from your coding agent

No command syntax. You talk to your agent in plain language and it calls Recallium on its own; send recallium by itself when you want the project context loaded again.

You want to	Say this
Reload project context	`recallium`
Start a session informed	Summarize the recent work, open follow-ups, and rules I should know.
Check before editing a file	What should I know before editing `src/auth/jwt.ts`?
Save a decision	Remember we chose Postgres over DynamoDB because the ledger needs strong consistency. Include the alternatives and the files we changed.
Find past work	How did we handle expired OAuth tokens, and why did we reject silent refresh?
Search uploaded documents	Search my documents for the API spec.
Find recurring problems	Why do authentication bugs keep returning? Look across prior fixes.
Think through a choice	Help me think through a gradual migration versus a full rewrite.
Track a follow-up	Create a task to migrate the remaining endpoints, linked to the token rotation decision.
Resume work	Where did we leave off?
Wrap up the day	Summarize what we accomplished and save a continuation point.

The recallium connector's tools listed in Claude Desktop's connector settings The same capabilities in every client: here, the recallium connector in Claude Desktop.

Five moments cover most of the habit: when you start a session, when you finish a piece of work, when you are about to edit a file, when you stop for the day, and when you return after a break. Save one decision, root cause, experiment or procedure at a time, with the reason and the files, while it is fresh.

Projects and workstreams

Record	Answers
Project	Which product or repository owns this context?
Workstream	Which body of work does this context explain?
Memory	What did we decide, learn, fix or prove?
Task	What action still needs to happen?

A project is the organization and access boundary. It usually maps to a repository; Recallium derives the name from the enclosing Git repository, and a clone can be mapped to an existing project with git config --local recallium.projectName payments-platform. Context from one project does not leak into another the user cannot access. Related projects can be linked as siblings or as parent and child while each keeps its own boundary.

A workstream is a named effort inside a project, such as oauth-migration or checkout-reliability. It groups the decisions, designs, fixes and checkpoints that explain one journey, and moves through planned, active, shipped or abandoned. Another session loads the workstream and sees its constraints, decisions and latest progress together.

Memory across the software lifecycle

Stage	What Recallium keeps	How agents use it
Plan and design	The approach the team chose and why	An agent proposing a change sees what was already decided and why
Build	What the team learned about the code, linked to the files it is about	Before an edit, search by topic and by file path
Review	Team rules	Rules load into every agent session, in every connected tool
Debug and incidents	The root cause, the fix, and the steps that worked	The next agent that hits the symptom finds the cause on the first search
Commit	`Recallium-Memory:` commit trailers	A commit links to the memories that explain it
Handoff	Workstreams, working state, session recap, tasks	A new session, agent or teammate resumes where the last one stopped
Reference	Uploaded documents	Specs and other files are searched alongside memories

On Recallium Cloud, insights across a project surface recurring approaches, recurring bugs with their causes and fixes, technical debt, and how an effort moved over time. Teams, projects and role-based access are managed there too.

Supported coding agents and IDEs

Client	macOS	Windows	Linux
Claude Code	✓	✓	✓
Codex CLI / Codex Work	✓	✓	✓
Cursor	✓	✓	✓
GitHub Copilot	✓	✓	✓
VS Code	✓	✓	✓
Claude Desktop	✓	✓	—
Antigravity, OpenCode, Hermes Agent, Devin Desktop, Cline, Zed, DeepSeek dsh, Droid (Factory), Kilo Code, Qwen Code	✓	—	✓

Continue.dev connects by manual setup. Any other MCP client can connect to the same endpoint; 60+ MCP clients are supported.

Where it helps

The incident at 2am. The root cause and the fix from the last time this symptom appeared are the first search result.
Handing off a half-finished migration. The workstream carries the constraints, the decisions and the working state to whoever picks it up, in whichever tool they use.
The decision that was already replaced. Agents follow the current decision, not the one in a stale comment.
Onboarding a new engineer. Their agent starts from what the team knows about the codebase on day one.
When a senior engineer leaves. What they worked out stays with the project.
Three tools, one memory. Research in Claude Desktop, build in Cursor, review in Claude Code, with one record across all three.
Conventions that hold without reminders. Team rules are loaded into every session, so reviewers stop repeating themselves.
The security review. Every decision has a date, an author, its files and its reasons.

Rules files and Recallium

CLAUDE.md, AGENTS.md, Cursor Rules and Copilot instructions hold standing instructions that one tool loads at the start of a session. They are the right place for those. Recallium holds what the team has learned since: the record agents produce while they work, searched on demand and shared across every tool and teammate. Keep both.

Retrieval

On LongMemEval-S, all 500 questions including abstention, Recallium finds the right memory for 499 (99.8% hit@10) and returns 98.6% of relevant sessions, from 3.8 results per question on average. Answer accuracy is 98.4% with a Claude Opus 5.5 reader and 90.2% with the official GPT-4o reader, under the official GPT-4o judge. Reader, judge, depth and dates are published at recallium.ai/benchmarks. Other vendors' reports use different readers, judges and depths, so they are not a controlled head-to-head ranking.

Privacy and data handling

The client sends two kinds of data to Recallium Cloud. Memory content is sent only when your agent explicitly saves a memory on your behalf. Client telemetry is edit metadata that links memories to the work in a session: file paths, hashes, edit and activity counts, and Git branch and commit provenance. The sensor does not send source file contents. npx -y recallium@latest status shows which server your client uses.

Recallium does not train AI models on customer memories and does not sell customer data. Tenants are isolated by row-level security; data is encrypted in transit and at rest on Google Cloud. Sharing follows the repository: a repository only you connect stays yours. A Data Processing Addendum and an availability policy are published.

Pricing

Cloud Free: 500 memories a month until December 2026, nothing to run. Cloud Pro: shared team memory, 5,000 memories a month, priced per engineer. recallium.ai/pricing.

FAQ

What is Recallium?

Institutional engineering memory for humans and AI agents. Decisions, root causes, fixes, constraints and rules captured in one session, in Claude Code, Codex, Cursor, GitHub Copilot or another MCP client, are recalled by every agent and teammate on the project in the next.

How do I add memory to Claude Code, Codex or Cursor?

Run npx -y recallium@latest install. It detects the agents on your machine, signs you in once and connects each one. Per-client guides are in the docs.

How is Recallium different from CLAUDE.md or Cursor Rules?

Rules files are instructions one tool loads at the start of a session. Recallium is the record agents produce while they work, searched on demand and shared across tools and teammates. Most teams keep both.

How is Recallium different from Mem0 or Supermemory?

Mem0 and Supermemory are memory APIs you build into an AI product so it remembers its users; both also ship Claude Code and Cursor plugins. Recallium is memory for the team building the product: it follows how engineering teams work, from design and decisions through debugging and shipping, with workstreams for handoffs, team rules in every session, commits linked to the memories behind them, and teams and role-based access on Recallium Cloud. The long form: Serving Memory vs. Engineering Memory.

What is an MCP memory server?

The Model Context Protocol is an open standard for connecting AI agents to tools and data. Recallium is an MCP server for team memory: one endpoint every connected agent reads and writes.

Can my team see my personal projects?

No. Sharing follows the repository. A repository your team connects on Cloud Pro is shared with the team; a repository only you connect stays yours. On Cloud Free nothing is shared.

Why is context missing when I switch tools?

Most missing-context problems across tools are project-scope mismatches. Use the same project name in every connected agent, or map the clone to the existing project once.

Is there a self-hosted version?

Yes. The community edition in community/ runs on Docker on your own machine or network, free under the Elastic License v2, and continues to be supported. See below.

Is Recallium the same as MiniMe MCP?

Yes. Recallium was called MiniMe MCP (also written MiniMe-MCP) from August 2025 until it was renamed. Existing MiniMe installations are the community edition and continue to be supported.

Self-hosted community edition (formerly MiniMe MCP)

The self-hosted community edition, which shipped as MiniMe MCP until the rename, continues to be supported. It lives in the community/ directory of this repository: a Docker deployment with its installation guide, the Claude Code skill and the Claude Desktop extension. The image is published on Docker Hub. It is free under the Elastic License v2 and runs on your own machine or network, including behind a corporate proxy or air-gapped; see the community README. Report issues for either edition on GitHub Issues.

Recallium Cloud is the managed service and carries the team features above: shared repositories, teams and role-based access, insights, and nothing to run. Moving your memories across takes one export and one import; see Migrating from the community edition to Recallium Cloud.

Migrating from the community edition to Recallium Cloud

Your projects and memories move from a self-hosted instance to Recallium Cloud as one zip file. Nothing is deleted from the self-hosted instance; it keeps running until you stop it.

1. Open Import/Export in the community dashboard. In your self-hosted dashboard, go to Projects and click Import/Export at the top right.

Community edition dashboard: the Projects page with the Import/Export button at the top right

2. Export all projects. On the Export tab, keep the scope at All Projects (a complete backup: projects, sessions, thinking sequences, thoughts, memories and project links) and leave the dates empty to export everything. The preview shows the record counts and size. Click Export and save the zip. The same export is available from the command line with community/install/download-memories.sh, which fetches it from your instance's /api/data/export endpoint.

Community edition Data Management dialog on the Export tab: scope All Projects, empty date range, a preview of projects, memories and sessions, and the Export button

3. Open Import/Export in Recallium Cloud. Sign in at app.recallium.ai, go to Projects and click Import/Export.

Recallium Cloud: the Projects page with the Import/Export button at the top right

4. Import the zip. On the Import tab, choose Select ZIP File to Import, pick the export from step 2 and click Import. Your projects appear under the same names, so the agents you connect next find them by the Git repository as before.

Recallium Cloud Data Management dialog on the Import tab with the Select ZIP File to Import control

5. Point your agents at Recallium Cloud. Run npx -y recallium@latest install. It connects the coding agents on the machine to Cloud and signs you in. If a clone's repository name differs from the imported project name, map it once with git config --local recallium.projectName <project-name> (docs). Then remove the self-hosted MCP entry from each client, or leave both connected while you compare.

Questions about a migration: [email protected].

Links


Website	recallium.ai
Why Recallium	recallium.ai/why-recallium
Memory for coding agents	recallium.ai/memory-for-coding-agents
Docs	docs.recallium.ai · index for agents
Pricing	recallium.ai/pricing
Changelog	recallium.ai/changelog
Community	Discord · r/recallium · X
Issues	GitHub Issues
Support	[email protected]

License

The community edition in community/ is licensed under the Elastic License v2: free to use and self-host; you may not offer it as a hosted service to third parties. Recallium Cloud is provided under its terms of service.

Serving memory

Engineering memory

Remembers

The person on the other side of the chat

Why the software is the way it is

Unit of memory

A fact about a user

A decision, a fix, a constraint, with its reasoning

Who reads it

Your product, on behalf of each end user

Every engineer and every coding agent on the team

What "current" means

The latest preference wins

The latest decision wins, and the old one stays on record

Scale

Millions of end users

One team, many repositories, many tools

Billed by

Requests, tokens, queries

Engineer

Cost of a stale memory

A slightly worse reply

A bug your security review already killed, shipped again

Command

Purpose

npx -y recallium@latest install

Detect coding agents, review the setup, connect them and sign in

npx -y recallium@latest status

Show client, sign-in, server and connected-agent state

npx -y recallium@latest doctor

Run capture-health and integration checks, with the repair for each failed one

npx -y recallium@latest login

npx -y recallium@latest update

Update when a newer client is available

npx -y recallium@latest uninstall

Open the Install / Modify screen and remove selected agents

npx -y recallium@latest uninstall --all

Remove all Recallium agent wiring and local Recallium state

You want to

Say this

Reload project context

recallium

Start a session informed

Summarize the recent work, open follow-ups, and rules I should know.

Check before editing a file

What should I know before editing src/auth/jwt.ts?

Save a decision

Remember we chose Postgres over DynamoDB because the ledger needs strong consistency. Include the alternatives and the files we changed.

Find past work

How did we handle expired OAuth tokens, and why did we reject silent refresh?

Search uploaded documents

Search my documents for the API spec.

Find recurring problems

Why do authentication bugs keep returning? Look across prior fixes.

Think through a choice

Help me think through a gradual migration versus a full rewrite.

Track a follow-up

Create a task to migrate the remaining endpoints, linked to the token rotation decision.

Resume work

Where did we leave off?

Wrap up the day

Summarize what we accomplished and save a continuation point.

Record

Answers

Project

Which product or repository owns this context?

Workstream

Which body of work does this context explain?

Memory

What did we decide, learn, fix or prove?

Task

What action still needs to happen?

Stage

What Recallium keeps

How agents use it

Plan and design

The approach the team chose and why

An agent proposing a change sees what was already decided and why

Build

What the team learned about the code, linked to the files it is about

Before an edit, search by topic and by file path

Review

Team rules

Rules load into every agent session, in every connected tool

Debug and incidents

The root cause, the fix, and the steps that worked

The next agent that hits the symptom finds the cause on the first search

Commit

Recallium-Memory: commit trailers

A commit links to the memories that explain it

Handoff

Workstreams, working state, session recap, tasks

A new session, agent or teammate resumes where the last one stopped

Reference

Uploaded documents

Specs and other files are searched alongside memories

Client

macOS

Windows

Linux

Claude Code

✓

Codex CLI / Codex Work

✓

Cursor

✓

GitHub Copilot

✓

VS Code

✓

Claude Desktop

✓

—

Antigravity, OpenCode, Hermes Agent, Devin Desktop, Cline, Zed, DeepSeek dsh, Droid (Factory), Kilo Code, Qwen Code

✓

—

✓

Website

recallium.ai

Why Recallium

recallium.ai/why-recallium

Memory for coding agents

recallium.ai/memory-for-coding-agents

Docs

docs.recallium.ai · index for agents

Pricing

recallium.ai/pricing

Changelog

recallium.ai/changelog

Community

Discord · r/recallium · X

Issues

GitHub Issues

Support

[email protected]