Search Memory vs Cognee

A side-by-side look at the Search Memory and Cognee MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

Search Memory logoSearch MemoryKnowledge & Memory · Local subprocess (stdio)Free web search and long-term memory for AI assistants. No API keys; data stays local.56GoodAuth: not declaredCognee logoCogneeKnowledge & MemoryMemory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources53GoodAuth: no auth required

Verdict: choose Search Memory for knowledge & memory work as a local process; choose Cognee for knowledge & memory. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

Search Memory logoChoose Search Memory when

  • You need dedicated capabilities in the Knowledge & Memory domain.
  • You prefer a local stdio subprocess transport.
  • You want tools like web_search, fetch_content, research.
Explore Search Memory

Cognee logoChoose Cognee when

  • You need dedicated capabilities in the Knowledge & Memory domain.
  • Its auth model fits you: No auth required.
  • You have the keys it needs: LLM_API_KEY.
  • You want tools like remember, recall, forget.
Explore Cognee

Feature & specification comparison

Rows where the two servers differ are marked.

SpecSearch Memory logoSearch MemoryCognee logoCognee
CategoryKnowledge & MemoryKnowledge & Memory
Quality signal56/100 · Good53/100 · Good
Install commandConfirmedNot confirmed yet
TransportLocal subprocess (stdio)—
AuthNot declaredNo auth required
PricingNot declaredFree
Required env varsNone listedLLM_API_KEY
Verified ownerCommunity listingCommunity listing
GitHub stars132,674
Directory activity 0 views 0 installs 0 upvotes 5 views 0 installs 0 upvotes
Tools124

Tools & capabilities

Search Memory tools 12

  • web_searchSearches the web and returns ranked results. Supports `strategy` (`fallback`/`aggregate`/`auto`), `domain`, `from_date`/`to_date`, `format` (`text`/`json`), and `deep=true` for source-backed answers.
  • fetch_contentFetches a URL and returns clean Markdown with content caching, charset handling, GitHub Raw fast paths, RSS feed extraction, and Playwright fallback.
  • researchResearches a question in one call: checks the local knowledge base, searches the web, reads the top pages (`max_sources`, default 3), answers with citations from both, and adds the pages it read to the knowledge base (`index=false` to skip; sources already indexed are not added again).
  • server_statusReturns provider availability, cache stats, knowledge index stats, memory stats, entity graph stats, recent search traces, browser state, routing profile metadata, feature flags, and uptime.
  • ingest_documentChunks a document and indexes it into the local knowledge base (FTS + vectors) and entity graph. Pass `content`, or `path` to a local PDF, DOCX, EPUB, HTML or text file inside `INGEST_ALLOWED_DIRS`.
  • index_urlFetches a URL and indexes its Markdown into the local knowledge base and entity graph.
  • search_indexHybrid keyword + semantic search over the local knowledge base; returns chunks with source citations. Supports `format: "json"`.
  • list_indexLists documents stored in the local knowledge base.
  • rememberStores a short fact or note in session memory.
  • recallSearches or lists session memory notes.
  • forgetDeletes a session memory note by id.
  • find_relatedExplores the entity graph: related documents and co-occurring entities for an entity name.

Cognee tools 4

  • rememberStore data in memory. Pass `data` for text, or `filename` + `content_base64` to ingest an uploaded file (up to 10 MB). With `session_id`: fast session cache (text only). Without `session_id`: permanent graph memory
  • recallSearch memory with auto-routing. Searches session cache first when `session_id` is provided, then falls through to the permanent graph
  • forgetDelete memory by dataset name or id, a single data item by `data_id` (paired with its `dataset_id`, both shown by `recall` with `include_references=True`), or delete all owned memory with `everything=True`
  • cognify_statusCheck the progress of background ingestion started by `remember(background=True)`. Unadvertised by default; discoverable via `search_tools` and callable by name

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

Search Memory

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "search-memory": {
      "command": "npx",
      "args": [
        "-y",
        "search-memory-mcp@latest"
      ]
    }
  }
}

Cognee

No confirmed install command for Cognee yet — follow the setup steps linked from its listing page rather than a guessed package name.

Frequently asked questions

Search Memory is categorized under Knowledge & Memory and uses a local stdio subprocess. Cognee belongs to Knowledge & Memory and uses an install path we have not confirmed yet. Pick Search Memory for knowledge & memory work and Cognee for knowledge & memory.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client. Cognee has no confirmed install command yet — follow its own setup instructions.

Search Memory has no declared pricing — check the project's own site. Cognee is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add search-memory and topoteretes-cognee as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, Search Memory has a quality signal of 56/100 (Good) with 0 views, 0 installs and 1 GitHub stars. Cognee has 53/100 (Good) with 5 views, 0 installs and 32,674 GitHub stars.