MCP Memory Service

Open-source persistent memory backend for AI agents that stores and retrieves context across sessions using hybrid BM25 + vector search, with optional Cloudflare sync for multi-device and multi-agent memory sharing.

Evaluated Mar 07, 2026 (0d ago) vlatest
Homepage ↗ Repo ↗ Other memory persistence vector-search chromadb sqlite cloudflare multi-agent knowledge-graph python
⚙ Agent Friendliness
77
/ 100
Can an agent use this?
🔒 Security
75
/ 100
Is it safe for agents?
⚡ Reliability
72
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
78
Documentation
80
Error Messages
62
Auth Simplicity
82
Rate Limits
70

🔒 Security

TLS Enforcement
88
Auth Strength
72
Scope Granularity
65
Dep. Hygiene
78
Secret Handling
72

Agent memory/persistence MCP. Stores potentially sensitive agent context. Local storage default — no network auth. For shared deployments, add auth layer. Encrypt sensitive memory payloads.

⚡ Reliability

Uptime/SLA
72
Version Stability
75
Breaking Changes
70
Error Recovery
72
AF Security Reliability

Best When

You have long-running AI agent workflows or multi-session projects where context loss between sessions is a significant friction point, and you want local-first storage with optional cloud sync.

Avoid When

You need a fully managed cloud memory service with zero infrastructure setup, or you are on Python 3.13 and cannot downgrade. Also avoid if macOS system Python is your only option (requires Homebrew Python for sqlite extensions).

Use Cases

  • Persisting project decisions and architectural context across Claude Code sessions without re-explaining
  • Multi-agent pipelines where multiple AI agents share a common memory store with typed causal relationships
  • Reducing token overhead by externalizing long-term context from the AI's context window
  • Team collaboration scenarios where AI memory is synchronized across devices via Cloudflare Workers KV
  • Ingesting and semantically searching across PDF, TXT, MD, and JSON knowledge documents

Not For

  • Users on Python 3.13 (sqlite-vec compatibility issue; use Python 3.12)
  • Simple single-session use cases where in-context memory is sufficient
  • Teams needing a fully managed SaaS memory solution (requires self-hosting)

Interface

REST API
Yes
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

Methods: none api_key oauth2
OAuth: Yes Scopes: No

Three modes: anonymous access (MCP_ALLOW_ANONYMOUS_ACCESS=true for local dev), API key (MCP_API_KEY env var for production), or OAuth 2.1 (MCP_OAUTH_ENABLED=true for team collaboration). HTTP dashboard requires auth by default. Local MCP usage can run without any auth.

Pricing

Model: open_source
Free tier: Yes
Requires CC: No

Apache 2.0 open source. Cloudflare sync feature may incur costs beyond free tier KV usage for high-volume memory stores.

Agent Metadata

Pagination
none
Idempotent
Partial
Retry Guidance
Not documented

Known Gotchas

  • Python 3.13 incompatible due to sqlite-vec missing pre-built wheels — use Python 3.12
  • macOS system Python lacks sqlite extension support — must use Homebrew Python
  • Cloudflare hybrid backend requires Cloudflare account setup before first use
  • MCP_MAX_RESPONSE_CHARS must be tuned or large memory retrievals can overflow agent context
  • Windows Claude Code users need a /session-start workaround for SessionStart hooks
  • X-Agent-ID header auto-tagging means multi-agent setups need careful agent identity management

Alternatives

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Scores are editorial opinions as of 2026-03-07.

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