xhs-bailian-mcp-server-cds007

xhs-bailian-mcp-server-cds007 is an MCP server package intended to expose some CDS007-related functionality to MCP-capable agents via the Model Context Protocol. No README/repo metadata content was provided here, so specific tools, inputs/outputs, and operational behavior cannot be verified.

Evaluated Apr 04, 2026 (17d ago)
Homepage ↗ Ai Ml mcp agent-tools cds007
⚙ Agent Friendliness
30
/ 100
Can an agent use this?
🔒 Security
28
/ 100
Is it safe for agents?
⚡ Reliability
18
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
45
Documentation
30
Error Messages
0
Auth Simplicity
30
Rate Limits
10

🔒 Security

TLS Enforcement
50
Auth Strength
30
Scope Granularity
20
Dep. Hygiene
20
Secret Handling
20

No concrete security implementation details (TLS requirements, auth scheme, secrets handling, dependency/CVE posture) were included in the supplied content.

⚡ Reliability

Uptime/SLA
0
Version Stability
30
Breaking Changes
20
Error Recovery
20
AF Security Reliability

Use Cases

  • Allowing MCP-capable AI agents to access CDS007-related operations as structured tools
  • Automating workflows that need CDS007 data/operations within an agent runtime
  • Integrating CDS007 functionality into agent toolchains via MCP

Not For

  • Direct human-facing application usage
  • Cases requiring a fully specified REST/GraphQL API contract (not evidenced here)
  • Security-sensitive deployments where auth, rate limits, and error semantics must be explicitly documented (not evidenced here)

Interface

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

Authentication

OAuth: No Scopes: No

Authentication method(s) and authorization model are not provided in the supplied content.

Pricing

Free tier: No
Requires CC: No

Pricing and hosting model are not provided in the supplied content.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Tool schemas, required arguments, and response formats are not provided here; agents may need to infer behavior or handle unexpected outputs.
  • Without documented rate limits and error semantics, agents may fail to back off/retry appropriately.

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

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