Search Memory vs Agent Recall
A side-by-side look at the Search Memory and Agent Recall MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Search Memory for knowledge & memory work as a local process; choose Agent Recall 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?
Choose 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.
Choose Agent Recall 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, session_end, remember.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Knowledge & Memory | Knowledge & Memory |
| Quality signal | 56/100 · Good | 69/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 371 |
| Directory activity | 0 views 0 installs 0 upvotes | 3 views 0 installs 0 upvotes |
| Tools | 12 | 5 |
| Full listing | View Search Memory | View Agent Recall |
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.
Agent Recall tools 5
session_start[ENTRY — call FIRST, before acting] Use when the user asks to start, load, continue, resume, or open memory for a project. Set mode='lite' for a ≤500-token briefing (good for fresh conversations where the agent will pull memory on demand via recall()).session_end[ON SAVE/EXIT — YOU must call this; nothing auto-saves] Use when the user asks to save, checkpoint, summarize, end, retain, or persist the current session. Optionally pass close_phase / open_phase to update the project pipeline narrative spine in the same call.remember[MID-SESSION WRITE — single fact/decision; saying it is not saving it] Use when the user asks to remember, store, note, or save a specific decision, fact, or insight.recall[RETRIEVE — use freely, any time] Use when the user asks to recall, search, find, or look up previous memory, context, or decisions.check[MID-SESSION — safe any time; for alignment, before risky decisions] Use when the user asks to validate understanding, verify alignment, or check if their interpretation matches the human's intent. Also call BEFORE a high-risk action — publish, deploy, delete, credential exposure, external send/message, or any other irreversible write — passing `action_description` (one sentence, what you're about to do). Returns matching corrections/rules/insights plus a `verdict`: `blocked` means an authoritative correction OVERRIDES the plan — read it before proceeding. To RECORD a durable human correction, pass `human_correction` as the STRUCTURED object {rule, why, applies_when} — a plain string is only STAGED for later review, never activated.
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": {
"search-memory": {
"command": "npx",
"args": [
"-y",
"search-memory-mcp@latest"
]
}
}
}
Agent Recall
{
"mcpServers": {
"agent-recall": {
"command": "npx",
"args": [
"-y",
"agent-recall-mcp"
]
}
}
}
Frequently asked questions
Search Memory is categorized under Knowledge & Memory and uses a local stdio subprocess. Agent Recall belongs to Knowledge & Memory and uses a local stdio subprocess. Pick Search Memory for knowledge & memory work and Agent Recall 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.
Search Memory has no declared pricing — check the project's own site. Agent Recall 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 agent-recall 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. Agent Recall has 69/100 (Great) with 3 views, 0 installs and 371 GitHub stars.