memory-graph

MemoryGraph is an MCP server for AI coding agents that provides persistent, graph-based memory. It lets agents store “memories” (typed items with tags/importance) and create relationships between memories, then retrieve them via recall/search tools (including an “extended” profile with more complex queries and DB statistics).

Evaluated Mar 30, 2026 (21d ago)
Repo ↗ Ai Ml ai-ml mcp memory knowledge-graph graph-database python coding-agents
⚙ Agent Friendliness
61
/ 100
Can an agent use this?
🔒 Security
52
/ 100
Is it safe for agents?
⚡ Reliability
18
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
78
Documentation
70
Error Messages
0
Auth Simplicity
80
Rate Limits
10

🔒 Security

TLS Enforcement
70
Auth Strength
50
Scope Granularity
30
Dep. Hygiene
60
Secret Handling
55

Security posture is only partially assessable from README/manifest snippets. TLS is likely assumed for any networked cloud endpoint but not explicitly documented. Auth appears optional (API key for cloud backend) without described scopes/least-privilege. No explicit guidance on logging of sensitive values or safe handling of secrets is included in the provided content. Dependency hygiene is plausible but unverified for CVEs in the supplied text.

⚡ Reliability

Uptime/SLA
0
Version Stability
40
Breaking Changes
0
Error Recovery
30
AF Security Reliability

Best When

You’re using an MCP-capable coding agent and you want structured, relationship-aware recall beyond flat text or basic retrieval.

Avoid When

You cannot control what the agent stores (or you don’t have a prompting/protocol strategy), and when you need fully documented production SLAs/error semantics beyond what the README shows.

Use Cases

  • Persisting decisions, bug fixes, and code patterns across agent sessions
  • Answering multi-hop questions by causal/relational chains (e.g., what led to a fix)
  • Auditing or reporting on knowledge coverage across a codebase
  • Assisting coding agents with retrieval-augmented memory for long-running projects

Not For

  • A standalone autonomous memory system that saves without agent/tool invocation
  • A generic vector-search service only (this is relationship/graph-oriented)
  • Production deployments where strict enterprise security/compliance needs are not documented

Interface

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

Authentication

Methods: Local/in-process tool usage (no auth described for SQLite/Core) Optional cloud backend via MEMORYGRAPH_API_KEY
OAuth: No Scopes: No

README references an API key for a future/coming cloud backend (memorygraph.dev). No detailed auth flows, scope models, or token handling guarantees are documented in the provided text.

Pricing

Free tier: No
Requires CC: No

Only a reference to a “free API key” signup at memorygraph.dev is mentioned; no pricing tiers/limits are provided in the supplied content.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • MCP tool providers don’t automatically store memories; the agent must be prompted/configured (e.g., via CLAUDE.md protocol) to use tools.
  • Persistence/behavior differs by backend mode (SQLite vs other backends); ensure correct backend configuration for multi-session expectations.
  • If relationships are important, the agent must explicitly create them (tool calls) rather than assuming they are inferred automatically.

Alternatives

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Scores are editorial opinions as of 2026-03-30.

8642
Packages Evaluated
17761
Need Evaluation
586
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