Synap Memory MCP Server
ai.maximem/synap
Persistent memory for AI agents — log and recall conversation context across sessions with ~15ms latency.
What is the Synap Memory MCP server?
Synap Memory is an MCP server that gives AI agents persistent memory lasting across conversations, sessions, and devices. It scores 92.0% on LongMemEval and 93.2% on LoCoMo, uses anticipatory retrieval to pre-fetch context before agents request it, and integrates with 24 agent frameworks via native SDKs and MCP.
Synap solves agent amnesia by storing and retrieving conversation context across time and sessions. It handles entity resolution (linking "my manager" to "Sarah" across conversations), temporal awareness (weighting recent context higher), and conscious forgetting (processing retractions). The MCP server exposes memory as four tools over Streamable HTTP, requiring only an API key—no local backend needed.
How to install Synap Memory
Copy-paste configuration for popular MCP clients.
AuthorizationrequiredsecretSynap API key as a Bearer token, e.g. 'Bearer synap_...'. From https://synap.maximem.ai
Tools & capabilities
Tools this server exposes to the agent.
log_exchange— Record a user message or agent response to persistent memory.recall_context— Fetch relevant context from memory based on a search query, user, and conversation scope.check_memory_status— Check the status and health of the memory system.list_recent_memories— List recent memories for a user or conversation.
Use cases
- Build voice AI agents that recall user context without awkward pauses, using ~15ms anticipatory retrieval.
- Enable multi-turn customer support agents to remember customer history, preferences, and past issues across sessions.
- Create long-running autonomous agents that maintain coherent context over days or weeks of operation.
- Implement no-code agent memory in Gumloop, n8n, or other MCP clients without writing SDK code.
- Support multi-tenant B2B platforms where memory is scoped across client → customer → user → conversation hierarchies.
Synap Memory MCP server FAQ
Synap Memory is a hosted memory layer for AI agents that persists conversation context across sessions and devices. It uses anticipatory retrieval to pre-fetch context before agents request it (~15ms P50 latency), handles entity resolution and temporal decay, and integrates via MCP, native SDKs, or framework-specific packages.
Synap offers a free Trial plan with 12,500 credits/month, 1 agent, and no card required. All plans—free and paid—include every Synap capability; plans differ only on volume and support.
Add the Synap MCP server URL (https://synap-mcp.maximem.ai/mcp) and your API key from the dashboard (https://synap.maximem.ai) to your MCP client configuration. The server exposes four tools: log_exchange, recall_context, check_memory_status, and list_recent_memories.
No. Synap is a fully hosted cloud service. The MCP server is a stateless adapter that forwards calls to the hosted Synap API; you only need an API key from the dashboard.
You need a Synap API key from https://www.maximem.ai/synap. The free Trial plan requires no credit card.
Synap ships native packages for 24 frameworks including LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Haystack, Google ADK, OpenAI Agents, Semantic Kernel, Pydantic AI, and others. For no-code platforms, use the MCP server.
README (reference)
Source of truth, from the repository.
The memory layer for production AI agents
Synap gives your agents memory that lasts across conversations, sessions and devices. It scores 92.0% on LongMemEval and 93.2% on LoCoMo (gpt-5-mini answer and judge, reproduce with our open harness), fetches context in ~15ms P50 (internal measurement) before your agent asks, and ships native packages for 24 agent frameworks.
<p align="center"> <strong>LangChain · LangGraph · LlamaIndex · CrewAI · AutoGen · Haystack · Google ADK · OpenAI Agents · Semantic Kernel · Pydantic AI · Agno · LiveKit · Pipecat · Claude Agent · Mastra · Vercel AI SDK · NeMo Agent Toolkit · Microsoft Agent Framework</strong> </p>What's open, what's hosted
| This repo (Apache 2.0) | Synap Cloud (managed) | |
|---|---|---|
| Python + JS SDKs, 24 framework packages, MCP adapter | ✅ open source | uses them |
| Memory engine: ingestion, entity resolution, retrieval, anticipation | — | ✅ runs here |
| What you need | pip install maximem-synap | an API key. Free Trial plan: 12,500 credits/month, 1 agent, no card required (pricing) |
Every plan, including the free one, gets every Synap capability. Plans differ on volume and support, not features.
Benchmarks
Synap's scores on the two standard long-term memory benchmarks, produced with our open-source harness on the official dataset releases.
| Benchmark | Synap accuracy | Scope |
|---|---|---|
| LongMemEval | 92.0% (460 / 500) | Full set, 6 categories |
| LoCoMo | 93.2% | Cat 1–4, adversarial excluded |
Other vendors publish their own numbers under different answer models and judges. Our harness ships adapters for Mem0, Zep and Supermemory, so you can run them side by side yourself. How scores differ across setups →
Category breakdown, methodology and every scope decision → eval_benchmark_runs_output
Install
# Python
pip install maximem-synap
# JavaScript / TypeScript
npm install @maximem/synap-js-sdk
Using a coding agent?
Paste this into Claude Code, Codex or Cursor:
<details> <summary><strong>Claude Code</strong></summary>Add Synap memory to this project. Run
pip install maximem-synap(ornpm i @maximem/synap-js-sdk), then install the Synap skill from https://github.com/maximem-ai/maximem_synap_sdk/tree/main/skills/synap and follow it to wire memory into the agent framework this repo uses. Ask me for my Synap API key when you need it.
git clone --depth 1 https://github.com/maximem-ai/maximem_synap_sdk /tmp/synap && cp -r /tmp/synap/skills/synap ~/.claude/skills/synap
</details>
<details>
<summary><strong>Codex</strong></summary>
git clone --depth 1 https://github.com/maximem-ai/maximem_synap_sdk /tmp/synap && mkdir -p ~/.agents/skills && cp -r /tmp/synap/skills/synap-codex ~/.agents/skills/synap
</details>
<details>
<summary><strong>Cursor / any MCP client</strong></summary>
Add the Synap MCP server URL and your API key from the dashboard. See packages/mcps/synap-mcp-server/.
60-second quickstart
Your agent forgets. Synap remembers across conversations, sessions, and devices.
The SDK connects to the hosted Synap cloud service, so you'll need an API key. There's no local server to run: memory processing happens in Synap's cloud, not in this package.
import asyncio
from maximem_synap import MaximemSynapSDK
sdk = MaximemSynapSDK(api_key="your-api-key")
async def main():
await sdk.initialize()
# Monday's standup
await sdk.conversation.record_message(
conversation_id="mon-standup",
user_id="alice",
role="user",
content="I'm migrating our auth service to OAuth2 this sprint.",
)
# Friday: completely different conversation, same user
context = await sdk.fetch(
conversation_id="fri-review",
user_id="alice",
search_query=["what is alice working on?"],
)
print(context.formatted_context)
# → "Alice is migrating the auth service to OAuth2 this sprint."
asyncio.run(main())
<details>
<summary><strong>JavaScript / TypeScript</strong></summary>
const { createClient } = require('@maximem/synap-js-sdk');
const client = createClient({ apiKey: 'your-api-key' });
await client.init();
// Record
await client.conversation.recordMessage({
conversationId: 'mon-standup',
userId: 'alice',
role: 'user',
content: "I'm migrating our auth service to OAuth2 this sprint.",
});
// Fetch later, anywhere
const context = await client.fetchUserContext({
userId: 'alice',
query: 'what is alice working on?',
});
console.log(context.formattedContext);
</details>
How it works: anticipatory memory
Most memory layers wait for the agent to ask. Synap works out what the agent will need next and has it ready. Six parts make that work.
🎯 Anticipatory Retrieval
Synap pre-fetches context before your agent requests it. ~15ms P50 latency in production (Maximem internal measurement). For voice AI agents, this is the difference between natural conversation and awkward pauses.
🔗 Entity Resolution
When a user says "my manager" in turn 3 and "Sarah" in turn 12, Synap resolves them automatically. Cross-session, cross-conversation, without the agent doing any work.
⏳ Temporal Awareness
Context from 30 minutes ago and context from 30 days ago should not carry equal weight. Synap applies temporal decay and relevance scoring so your agent surfaces the right information at the right time.
🧠 Conscious Forgetting
When a user says "ignore what I said about the budget," Synap processes that as a retraction, not just more context to store. Contradiction handling is built into the pipeline.
🏗️ Custom Memory Architectures
No universal memory model. Synap builds customized memory architectures per use case. Customer support agents and voice AI agents need different context strategies. Synap handles both.
🏢 Multi-Tenant Scoping
Built for B2B from day one. Memory is scoped across a four-level hierarchy:
client → shared knowledge across your entire platform
└── customer → per-company context (multi-tenant B2B)
└── user → per-user memory and preferences
└── conversation → in-session history
One fetch() call merges all relevant scopes in parallel.
Framework integrations
Installable packages, not code snippets. Deep framework surfaces with callbacks, graph nodes, retrievers, memories, and plugins.
LangChain
pip install maximem-synap maximem-synap-langchain
from maximem_synap import MaximemSynapSDK
from synap_langchain import SynapChatMessageHistory
from langchain_openai import ChatOpenAI
from langchain_core.runnables.history import RunnableWithMessageHistory
sdk = MaximemSynapSDK(api_key="your-api-key")
await sdk.initialize()
chain = RunnableWithMessageHistory(
ChatOpenAI(),
lambda session_id: SynapChatMessageHistory(
sdk=sdk, conversation_id=session_id, user_id="alice",
),
)
CrewAI
pip install maximem-synap maximem-synap-crewai
from synap_crewai import SynapStorageBackend
crew = Crew(
agents=[...], tasks=[...],
memory=True,
storage=SynapStorageBackend(sdk=sdk, user_id="alice"),
)
LlamaIndex
pip install maximem-synap maximem-synap-llamaindex
from synap_llamaindex import SynapChatMemory
memory = SynapChatMemory(sdk=sdk, user_id="alice")
agent = ReActAgent.from_tools(tools, memory=memory)
All integrations
<!-- BEGIN integrations (generated by scripts/gen_readme_integrations.py) -->| Framework | Package | Install |
|---|---|---|
| LangChain | maximem-synap-langchain | pip install maximem-synap-langchain |
| LangGraph | maximem-synap-langgraph | pip install maximem-synap-langgraph |
| LlamaIndex | maximem-synap-llamaindex | pip install maximem-synap-llamaindex |
| CrewAI | maximem-synap-crewai | pip install maximem-synap-crewai |
| AutoGen | maximem-synap-autogen | pip install maximem-synap-autogen |
| Haystack | maximem-synap-haystack | pip install maximem-synap-haystack |
| Google ADK | maximem-synap-google-adk | pip install maximem-synap-google-adk |
| OpenAI Agents SDK | maximem-synap-openai-agents | pip install maximem-synap-openai-agents |
| Semantic Kernel | maximem-synap-semantic-kernel | pip install maximem-synap-semantic-kernel |
| Pydantic AI | maximem-synap-pydantic-ai | pip install maximem-synap-pydantic-ai |
| Agno | maximem-synap-agno | pip install maximem-synap-agno |
| LiveKit Agents | maximem-synap-livekit-agents | pip install maximem-synap-livekit-agents |
| Pipecat | maximem-synap-pipecat | pip install maximem-synap-pipecat |
| Claude Agent (Python) | maximem-synap-claude-agent | pip install maximem-synap-claude-agent |
| Claude Agent (TypeScript) | @maximem/synap-claude-agent | npm i @maximem/synap-claude-agent |
| Mastra | @maximem/synap-mastra | npm i @maximem/synap-mastra |
| Vercel AI SDK | @maximem/synap-vercel-adk | npm i @maximem/synap-vercel-adk |
| Vercel eve | @maximem/synap-eve | npm i @maximem/synap-eve |
| NVIDIA NeMo Agent Toolkit | maximem-synap-nemo-agent-toolkit | pip install maximem-synap-nemo-agent-toolkit |
| Microsoft Agent Framework | maximem-synap-microsoft-agent | pip install maximem-synap-microsoft-agent |
| Strands Agents | maximem-synap-strands-agents | pip install maximem-synap-strands-agents |
| CAMEL-AI | maximem-synap-camel-ai | pip install maximem-synap-camel-ai |
| Smolagents | maximem-synap-smolagents | pip install maximem-synap-smolagents |
| Deepagents | maximem-synap-deepagents | pip install maximem-synap-deepagents |
| Remote MCP Server | maximem-synap-mcp-server | pip install maximem-synap-mcp-server |
MCP server
Give no-code and low-code agents (Gumloop, n8n, and any MCP-compatible client) persistent memory with nothing but an MCP URL and your Synap API key. No SDK, no code. The server exposes Synap's memory as four MCP tools (log_exchange, check_memory_status, recall_context, list_recent_memories) over Streamable HTTP.
It's a stateless adapter over the hosted Synap API: each call maps to one REST operation and your Bearer token is forwarded verbatim, so there's no separate backend to run. Use the managed endpoint (grab the URL and token from your dashboard), or self-host the adapter from source.
→ Source & self-hosting: packages/mcps/synap-mcp-server/
Deep dives
Understand the system before building on it:
- 📘 Why we built Synap: the problem with current AI memory systems
- ⚙️ How Synap works under the hood: architecture, retrieval pipeline, and design decisions
- 📊 Benchmark results: 92.0% on LongMemEval, 93.2% on LoCoMo, methodology, and reproducibility
- 🧪 Evaluation harness: run LoCoMo and LongMemEval yourself against Synap, Mem0, Zep and Supermemory
Agent skills
Drop-in instructions that teach coding agents how to wire Synap into your codebase. Install steps are in Using a coding agent?.
- Synap skill for Claude Code: SDK setup, scoping (User/Customer/Client), ingestion, retrieval, and one-page wiring guides for all supported frameworks.
- Synap skill for Codex: the same guide, packaged for Codex (
~/.agents/skills/synap).
Requirements
- Python SDK: Python 3.11+
- JavaScript SDK: Node 20+ (Python 3.11+ for the bridge layer)
- A Synap API key: get one at maximem.ai
Resources & community
- 📖 Documentation
- 🚀 Dashboard
- 💬 GitHub Discussions: questions, ideas, show what you built
- 🔒 Security policy
- 🤖 AGENTS.md and llms.txt for coding agents
- 𝕏 Twitter / X
Contributing
This repo is a published mirror of Maximem's monorepo, so everything under packages/ is overwritten on each sync and pull requests against it are closed. Bug reports, gaps, and new-framework requests are very welcome as issues, and questions go to Discussions. See CONTRIBUTING.md for how to run the code locally and what a new integration needs.
License
Apache 2.0 (see LICENSE). Each package declares its own license in its metadata; the core Python and JS SDKs and the Vercel AI SDK integration are MIT.
<p align="center"> Built by <a href="https://www.maximem.ai"><strong>Maximem AI</strong></a> </p>
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