ai-recallworks 0.3.3

Open-source agent-memory MCP server. recall.works

Recall™

Open-source memory for AI agents. MCP-native. Self-hosted. One Docker image.

OSS quickstart · Recall Pro → · Book a demo · IceWhisperer for Encompass

Your agent forgets every session. Recall fixes that — with a small, opinionated memory surface that any MCP-speaking agent (or any HTTP client) can drive. Append-only, rebuildable, soft-delete by design.

   ┌─────────────┐    MCP / HTTP    ┌──────────────────────────┐
   │  AI agent   │ ───────────────► │  Recall (one container)  │
   │  (Copilot,  │                  │   • 13 memory tools      │
   │   Claude,   │  remember/recall │   • BYO embedder + LLM   │
   │   Cursor,   │ ◄─────────────── │   • Append-only artifacts│
   │   custom)   │                  │   • Auto-snapshot to disk│
   └─────────────┘                  └──────────────────────────┘

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Five-minute install

1. Run the server:

docker run -d --name recall \
  -p 8787:8787 \
  -e API_KEY=changeme \
  -v recall-data:/data \
  ghcr.io/recallworks/recall:latest

2. Talk to it — pick your stack:

# Raw HTTP (any language)
curl -H "X-API-Key: changeme" \
     -H "Content-Type: application/json" \
     -d '{"content":"first memory","tags":"hello"}' \
     http://localhost:8787/tool/remember

# Python
pip install recall-client

from recall_client import RecallClient
with RecallClient("http://localhost:8787", api_key="changeme") as c:
    c.remember("first memory", tags="hello")
    print(c.recall("memory").result)

// TypeScript / JavaScript (Node 18+, Bun, Deno, browser)
npm install @recallworks/recall-client

import { RecallClient } from "@recallworks/recall-client";
const c = new RecallClient({ baseUrl: "http://localhost:8787", apiKey: "changeme" });
await c.remember("first memory", { tags: "hello" });
console.log((await c.recall("memory")).result);

Full walkthrough: docs/quickstart.md.

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What you get

• 13 tools — remember, recall, reflect, anti_pattern, checkpoint, pulse, session_close, index_file, reindex, snapshot_index, memory_stats, forget, maintenance.
• Two transports — plain HTTP (POST /tool/{name}) and MCP over SSE. Drop into Copilot, Claude Code, Cursor, or any MCP client.
• Bring your own models — pluggable embedder (default / OpenAI / Ollama) and summarizer (noop / OpenAI / Ollama). Run fully offline, fully on-prem, or against your own Azure-OpenAI tenant. See docs/byo-models.md.
• Durable by default — ephemeral live store with auto-snapshot to disk; container restarts come up whole.
• Append-only artifacts — every write also lands as a .md file. If the vector store ever burns down, reindex rebuilds it from the artifacts.
• forget is soft-archive — guardrail wired into the OSS code itself, not bolted on as policy. Memory you delete can be recovered.

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How it's different

	Recall	Mem0 / Letta / Zep
License (core)	MIT	mixed; SaaS-first
Self-host	one docker run	varies, often non-trivial
BYO embedder	default / OpenAI / Ollama (env var)	usually fixed
BYO LLM	noop / OpenAI / Ollama (env var)	usually fixed
Storage model	append-only artifacts + vector index, rebuildable	live DB only
delete	soft-archive by design	hard delete
Tool surface	13 opinionated tools (memory + workflow)	embedding + retrieval primitives
MCP-native	yes, plus plain HTTP	partial / via wrapper
Ops model	single binary, single container	multi-service stack

If you want a managed service, see Recall Cloud below. If you want a brain you fully own, this OSS core is enough.

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Repo layout

Path	What
src/recall/	OSS server (MIT)
src/recall/tools/	One module per tool
src/recall/transport/	HTTP + MCP/SSE adapters
docker/single-tenant/	Reference Dockerfile + compose
tests/	pytest suite (no Docker required)
docs/	Quickstart, conventions, architecture
enterprise/	Multi-tenant, SSO, control plane (BSL)

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Conventions

These are the practices that make the tools pay off. Pick what fits.

• Cold-start ritual — opening protocol every session should run.
• Branding — signed-edit headers so you can trace which agent touched which file when.

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Status

Alpha. The code in src/recall/ is extracted from a hosted production brain that has served thousands of sessions, then sanitized of org-specific paths, extensions, and tenant data. Expect breaking changes before 1.0; pin the image tag.

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Contributing

Yes — please read CONTRIBUTING.md first. We accept bug fixes, new Store backends, doc improvements, and anti-pattern entries. We don't accept architectural rewrites without prior discussion.

Security issues: see SECURITY.md.

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License

• src/recall/, clients/, docker/single-tenant/, docs/, examples/ — MIT (LICENSE)
• enterprise/ — BSL 1.1, 5-seat additional-use grant, converts to MIT after 3 years (LICENSE-COMMERCIAL.md)

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Recall Open Source vs. Recall Pro vs. Hosted

Capability	OSS (this repo)	Recall Pro	Recall Cloud
Single-tenant Docker image	✅	✅	n/a (hosted)
13 memory tools, MCP + HTTP	✅	✅	✅
BYO embedder + LLM	✅	✅	✅
Append-only artifacts + auto-snapshot	✅	✅	✅
Multi-tenant, SSO, RBAC	—	✅	✅
Audit log + retention policy	—	✅	✅
Cross-session entity graph	—	✅	✅
PII sanitization pipeline	—	✅	✅
Snapshot replication / DR	—	✅	✅
Vendor support + SLA	community	business hours	24×7
Hosted on our infra	—	—	✅
Pricing	free	from $99/mo per node	from $0.10 per 1k tools

Recall Pro ships from the enterprise/ tree under a Business Source License — source-available, 5-seat free Additional Use Grant, converts to MIT after 3 years. Buy a license and the enterprise/ modules light up alongside your OSS install.

Recall Cloud is the hosted multi-tenant version. Same tools, no infra. Reach out for early-access pricing.

➡️ Talk to sales: [e-mail] · Book a 20-min walkthrough: https://recall.works/demo

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Vertical builds powered by Recall

Recall is the engine. We ship turn-key vertical brains on top of it:

• IceWhisperer — the memory + workflow brain for ICE Mortgage Technology / Encompass shops. Pre-loaded SDK index, settings recipes, plugin audits, drift detection. Pilots from $250/mo.

If you want a vertical brain for your industry, we'll build it. Email [e-mail].

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Maintainers

Reach the maintainers at [e-mail]. Issues and PRs welcome on GitHub.