Engram vs AgentRecall
A side-by-side look at the Engram and AgentRecall MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Engram for knowledge & memory work as a local process; choose AgentRecall 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 Engram when
- You need dedicated capabilities in the Knowledge & Memory domain.
- You prefer a local stdio subprocess transport.
- You want tools like
create_conversation, append_messages, search.
Choose 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.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Knowledge & Memory | Knowledge & Memory |
| Quality signal | 57/100 · Good | 68/100 · 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 | 19 | 372 |
| Directory activity | 2 views 0 installs 0 upvotes | 5 views 0 installs 0 upvotes |
| Tools | 6 | 5 |
| Full listing | View Engram | View AgentRecall |
Tools & capabilities
Engram tools 6
create_conversationStart a new conversation with optional title, tags, metadataappend_messagesAdd messages to an existing conversationsearchSemantic search across all conversationsget_conversationRetrieve a conversation with its messageslist_conversationsList conversations with filtering and paginationdelete_conversationRemove a conversation and its data
AgentRecall tools 5
session_startLoads corrections, insights and `watch_for` warnings for the projectrememberSaves one fact; auto-routes to journal / palace room / corrections / awarenessrecallRanked search across every store (RRF), with `useful` feedback that re-weights future rankingcheckMatches the plan against known corrections; returns `verdict: "blocked"` when one overrides itsession_endWrites the journal, promotes insights, records trajectory, optionally opens/closes a pipeline phase
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.
Engram
{
"mcpServers": {
"engram-2": {
"command": "npx",
"args": [
"-y",
"@getengram/cli"
]
}
}
}
AgentRecall
{
"mcpServers": {
"goldentrii-agentrecall": {
"command": "npx",
"args": [
"-y",
"agent-recall-mcp"
]
}
}
}
Frequently asked questions
Engram is categorized under Knowledge & Memory and uses a local stdio subprocess. AgentRecall belongs to Knowledge & Memory and uses a local stdio subprocess. Pick Engram for knowledge & memory work and AgentRecall 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.
Engram has no declared pricing — check the project's own site. AgentRecall 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 engram-2 and goldentrii-agentrecall as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Engram has a quality signal of 57/100 (Good) with 2 views, 0 installs and 19 GitHub stars. AgentRecall has 68/100 (Great) with 5 views, 0 installs and 372 GitHub stars.