zmp-knowledge-store-mcp-server

MCP server intended to expose a “knowledge store” for use by AI agents via the Model Context Protocol. It likely provides tools for adding, retrieving, or searching knowledge/data, backed by some persistence layer.

Evaluated Apr 04, 2026 (17d ago)
Homepage ↗ Ai Ml mcp ai-agents knowledge-base rag tooling
⚙ Agent Friendliness
37
/ 100
Can an agent use this?
🔒 Security
28
/ 100
Is it safe for agents?
⚡ Reliability
25
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
60
Documentation
40
Error Messages
0
Auth Simplicity
50
Rate Limits
0

🔒 Security

TLS Enforcement
60
Auth Strength
20
Scope Granularity
0
Dep. Hygiene
30
Secret Handling
30

No repository/package security details were provided here. Assume you must verify: transport security (TLS), authentication/authorization, input validation, logging/redaction of secrets, and dependency vulnerability status.

⚡ Reliability

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

Use Cases

  • Connect an AI agent to a knowledge base via MCP tools
  • RAG-style knowledge retrieval with an agent
  • Centralize knowledge storage and allow agents to query it
  • Programmatically manage knowledge entries through an agent tool interface

Not For

  • Direct production usage without validating storage and data-handling semantics
  • Use as a general-purpose database without knowledge-specific operations
  • Environments requiring strong compliance guarantees unless explicitly documented

Interface

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

Authentication

OAuth: No Scopes: No

No authentication details provided in the supplied information; MCP servers commonly require local/explicit configuration, but this cannot be confirmed here.

Pricing

Free tier: No
Requires CC: No

No pricing information provided.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Without explicit tool schemas and examples, agents may mis-handle required parameters.
  • Knowledge stores often have eventual consistency or indexing delays; agents may need to retry retrieval after ingestion.
  • If idempotency is not documented, repeated writes during agent retries may create duplicates.

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Scores are editorial opinions as of 2026-04-04.

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