CSCognee Space

Independent, unofficial Cognee companion

Cognee Space

Give AI agents memory your team can trust: source ingestion, knowledge graph RAG, recall modes, MCP memory access, feedback loops, and self-hosted controls in one paid planner.

View pricing packages Preview the planner Review keyword evidence

Traffic keyword rule

Built from strong-relevance keyword candidates

Cognee Space uses the Skill rule for traffic terms: a term must match the SaaS theme, have a unique landing page, and carry MiroFish proof before it can be called validated. Current pages use strong-relevance candidates while the MiroFish values remain pending.

6primary keyword candidates
8long-tail keyword candidates
0validated traffic keywords until MiroFish proof lands
strongtheme relevance required for every counted term

Pricing required

Trusted AI memory planner preview

The planner is gated until a package is selected and Polar checkout is verified. The preview shows the required inputs without returning a full production plan.

{
  "status": "pricing_required",
  "next": "Choose a pricing package before using the planner.",
  "pricing": "/pricing/"
}

Page matrix

Keyword-to-page landing matrix

AI memory

Primary landing page for AI memory, persistent AI memory for agents, and Cognee memory lifecycle terms.

Open AI memory

Knowledge graph RAG

Primary landing page for knowledge graph RAG and knowledge graph RAG planner terms.

Plan Graph RAG

MCP memory server

Primary landing page for MCP memory server and Cognee MCP memory server terms.

Review MCP setup

Agent memory

Primary landing page for agent memory and AI agent long term memory terms.

Plan agent memory

Self-host Cognee

Primary landing page for self-host Cognee, AI memory deployment checklist, and private rollout intent.

Review self-hosting

Keyword evidence

Shows source, validation state, theme relevance, unique landing page, and MiroFish proof status for each candidate.

Open evidence

Model context

Keep memory plans aligned with the model layer

Memory and knowledge-graph teams comparing model context windows can use the Kimi K3 resource hub before deciding how much source material to pass into agent memory.