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Smithery vs Cognee

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Smithery compared with Cognee
DetailSmithery logo Smithery Cognee
What it doesConnect agents to thousands of tools and services with managed authentication and credentials Open-source memory platform for AI agents
StageNot given Not given
FoundedNot given Not given
Based inNot given DE
Pricing modelFreemium Not given
PricingHobby: Free (50K RPCs/month, 3 Namespaces, Managed OAuth, Persistent connections); Pay as you Go: $10/mo (100K RPCs/month included, then $0.10 per 1K RPCs, 100 Namespaces, Managed OAuth, Persistent connections); Custom: Contact for pricing (Everything in Pay as you Go plus custom rate limits, uptime Free: $0/month with 1M tokens and 1 workspace (no card required). Standard: $1.00 per 1M tokens plus $5 per additional workspace. Enterprise: contact for pricing with bring-your-own-cloud deployment. Open-source engine available free to self-host.
Key features
  • Managed OAuth and credential storage
  • Persistent connections
  • Public MCP registry with hundreds of pre-built services
  • Compatible with Claude, Cursor, and MCP-compatible AI assistants
  • Multiple namespace support
  • RPC-based usage model
  • Unified vector search, knowledge graphs, and relational storage
  • Automatic knowledge graph generation from data sources
  • Multi-tenant support with isolated workspaces
  • Data source integrations (Slack, Notion, Google Drive, GitHub, etc.)
  • Self-improving memory that learns from use
  • Multiple deployment options (cloud, self-hosted, air-gapped)
  • Agent framework integrations (LangGraph, CrewAI, OpenAI SDK, MCP)
  • Support for multiple vector and graph databases
  • GDPR compliance and encryption at rest and in transit
  • Built-in graph visualization of company brain
What makes it different
  • Handles authentication and credential complexity for agents
  • Unified interface to thousands of tools and services
  • Public registry of MCP servers for easy discovery
  • Free tier available for getting started
  • Combines vectors with graph relationships and generated data models for connected context retrieval
  • State of the art performance on BEAM benchmark (79% vs 73.4% at 100k tokens)
  • Keeps memory costs flat as data grows compared to baseline LLM approaches
  • Fully open-source with no database lock-in
  • Updates memory as source data changes, not just static snapshots
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)79 no change since last check70 no change since last check
Trust Flow (Majestic)2414
Citation Flow (Majestic)5543
Referring domains (Majestic)37751089

4 details filled in for both companies.

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