AgentRecall vs Search Memory

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

AgentRecall logoAgentRecallKnowledge & Memory · Local subprocess (stdio)Persistent, compounding memory for AI agents across sessions. Uses the Intelligent Distance Protocol to surface the most contextually relevant past memories. Five tools: sessionstart, remember, recall, check, sessionend. npx agent-recall-mcp68GreatAuth: no auth requiredSearch 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 declared

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

Which MCP server should you choose?

AgentRecall logoChoose AgentRecall when

  • You need dedicated capabilities in the Knowledge & Memory domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: No auth required.
  • You want tools like session_start, remember, recall.
Explore AgentRecall

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

Feature & specification comparison

Rows where the two servers differ are marked.

SpecAgentRecall logoAgentRecallSearch Memory logoSearch Memory
CategoryKnowledge & MemoryKnowledge & Memory
Quality signal68/100 · Great56/100 · Good
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthNo auth requiredNot declared
PricingFreeNot declared
Required env varsNone listedNone listed
Verified ownerCommunity listingCommunity listing
GitHub stars3711
Directory activity 5 views 0 installs 0 upvotes 0 views 0 installs 0 upvotes
Tools512

Tools & capabilities

AgentRecall tools 5

  • session_startLoads corrections, insights and `watch_for` warnings for the project
  • rememberSaves one fact; auto-routes to journal / palace room / corrections / awareness
  • recallRanked search across every store (RRF), with `useful` feedback that re-weights future ranking
  • checkMatches the plan against known corrections; returns `verdict: "blocked"` when one overrides it
  • session_endWrites the journal, promotes insights, records trajectory, optionally opens/closes a pipeline phase

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.

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.

AgentRecall

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "goldentrii-agentrecall": {
      "command": "npx",
      "args": [
        "-y",
        "agent-recall-mcp"
      ]
    }
  }
}

Search Memory

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

Frequently asked questions

AgentRecall is categorized under Knowledge & Memory and uses a local stdio subprocess. Search Memory belongs to Knowledge & Memory and uses a local stdio subprocess. Pick AgentRecall for knowledge & memory work and Search Memory 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.

AgentRecall is listed as free. Auth: no auth required. Search Memory has no declared pricing — check the project's own site. 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 goldentrii-agentrecall and search-memory as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, AgentRecall has a quality signal of 68/100 (Great) with 5 views, 0 installs and 371 GitHub stars. Search Memory has 56/100 (Good) with 0 views, 0 installs and 1 GitHub stars.