Connect-MCP

WorkingMemory

ai.workingmemory/memory · v1.0.0

Persistent personal memory for AI assistants — save, search, and recall across every MCP client.

MCPremoteno credentialsTasks & projectsKnowledge & docsEmail

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 4 tools, protocol 2025-11-25 · checked 2026-10-17

Test & rating

B 88/100

What it does: 4 tools · 1 read, 3 write (incl. delete/pay) · Knowledge & docs, Tasks & projects, Email

No tool could be tested safely. Only read-only tools that need no input are called.

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +10
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +10
  • Read/write annotations: +5
  • Safe test call: +8
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://app.workingmemory.ai/mcp

Tools

4 tools listed at last check
  • save_memory Save a thought, insight, fact, or todo to the user's Working Memory. The text is parsed and stored as one or more structured memory items, searchable a moment later via search_memory. Also use this when the user pastes memories or notes brought from another assistant — pass the full pasted text; it
  • search_memory Search the user's Working Memory for relevant past notes and facts. Use this when the user references something they may have stored earlier, or to find related context before answering. Always include your conversation id in client.conversation_id.
  • manage_memory Manage an existing memory item. Currently supports deleting a memory by id (soft delete — recoverable for 30 days). Use search_memory to find the id first.
  • capture_memory Capture durable facts from a task you just completed (drafting an email, summarizing a document, making a decision), as a byproduct — the user does nothing. Pass the task output/content; durable facts are extracted and stored automatically. Always include your conversation id in client.conversation_

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