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Side-by-side MCP evidence comparison
Evidence fieldCogneeShortlist candidatecodaMCP100 Recommended
Task fit
Best for
  • Teams that want persistent graph-based memory/knowledge retrieval across AI sessions and can govern stored data.
  • Collaborative document and structured-table workflows in Coda.
Not ideal for
  • Workloads that require stateless operation or cannot persist project/user information in a memory graph.
  • Teams outside the publisher ecosystem or without least-privilege credentials
Avoid when
  • Do not ingest sensitive data without understanding where the selected Cognee deployment stores graph/vector/content data and who can query it.
  • The connected identity is broader than the task requires
  • Tool calls cannot be reviewed before consequential mutations
Provenance
Provenance details

First-party MCP

github:topoteretes · Publisher source ↗

First-party MCP

ecosystem:coda · Publisher source ↗

Maintenance
Maintenance details

Repo: Not documented

Package: Not documented

Repo: Not documented

Package: Not documented

Popularity evidence
Package downloads / 30 days

1,288

package downloads / 30 days · checked 2026-10-21

No reliable download data
Shared repository stars

32,633

Shared repository stars (not MCP-specific) · checked 2026-10-21

Not documented
Client coverage
Client coverage detailsNot documented
Claude Code✓ Streamable HTTP
Claude Desktop✓ Streamable HTTP
Codex✓ Streamable HTTP
VS Code✓ Streamable HTTP
Cursor✓ Streamable HTTP
OpenCode✓ Streamable HTTP
Client coverage noteLocal stdio runs on your computer. Streamable HTTP connects to a remotely hosted MCP server.
Access and data
AuthenticationCloud-backed configuration can use Cognee API key headers; self-hosted HTTP deployments can use documented Bearer-token/auth modes.The official hosted endpoint supports OAuth 2 and personal access tokens.
CostOpen-source/self-hosted infrastructure or Cognee cloud plan plus model/provider costs may apply.The MCP integration has no separately verified MCP100 price conclusion. Publisher subscriptions, API usage, compute, storage, and AI-client charges may apply.
PermissionsCan ingest, persist, query and in some modes delete/manage memory datasets according to deployment credentials.Coda document sharing, user permissions, admin controls, and OAuth or PAT scope determine access.
Data handlingContent supplied to Cognee can be persisted in graph/vector/storage backends; retention and tenant isolation depend on the deployment.Authorized service data and tool results pass through the MCP server to the connected AI client. Review the publisher and client data policies before using sensitive files & knowledge information.
Limitations
Tradeoffs
  • Promoted after strict re-audit: canonical identity and MCP-native/publisher-backed implementation are sufficiently evidenced, with real workflow value, usable documentation, understandable permissions, plausible maintenance, and no unresolved security veto. Still not strong enough for Recommended.
  • Documents and tables can contain broad internal knowledge, and write tools can alter shared operational records.
Risk contextPersistent memory can retain sensitive project/user information beyond the current conversation.Documents and tables can contain broad internal knowledge, and write tools can alter shared operational records. Use a test environment where practical, least-privilege credentials, narrowly enabled tools, and explicit confirmation for mutations. MCP100 did not execute third-party server code during this documentation review.
Evidence date
Editorial review2026-10-212026-07-30
Candidate evidence2026-10-21T00:00:00Z2026-09-24T04:25:05.554391Z

Popularity, maintenance, fit, permissions, and client support are independent evidence fields.

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