workingmemory
Registry code: 1b834bb526c6878a
Working Memory is the user's persistent memory, shared across every AI tool they use.
- search_memory: before answering anything that depends on the user's own context (their projects, people, preferences, commitments), search first. Do not guess at facts you could look up.
- endpoint
- https://app.workingmemory.ai/mcp
- protocol
- streamable-http ·2025-11-25
- authentication
- none observed
- public key
- none — nobody has proven they own this listing · is it yours? claim it
- karma
- 0 · newcomer
- Is workingmemory live?
- Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.
- Is workingmemory free to use?
- Not anonymously — it asks for a key or a login before it will serve. Whether that key costs anything is the operator's plan to say: the hub measured the door, not the pricing.
- What tools does workingmemory have?
- 4 tools: save_memory, capture_memory, manage_memory, search_memory.
- Is workingmemory safe to connect?
- The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
90 days 99.2%· all time 99.2%
last good check
of 4 tools
- degraded → live
- degraded → live
- live → degraded· timeout after 20000ms
- degraded → live
- live → degraded· timeout after 20000ms
- topic
- ai & agents memory & context
- used for
- search the user's persistent memory
- save a fact to memory
- capture facts from a finished task
- delete a memory item
- takes → gives
- text → text
- tools
- 1 reads3 changes data
Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.
through this hub
successful
what callers paid
Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.
search_memory reads auth-required 5h ago
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.
{ "type": "object", "required": [ "query" ], "properties": { "k": { "type": "number", "description": "Max results (1–20). Defaults to a sensible value." }, "query": { "type": "string", "description": "Semantic query." }, "client": { "type": "object", "properties": { "conversation_id": { "type": "string", "description": "Opaque identifier; typically the client's conversation thread ID." }, "conversation_title": { "type": "string", "description": "Human-readable conversation title (max 200 chars; longer values truncated server-side)." } }, "description": "Context about the CURRENT client session. Pass your conversation/thread id as `conversation_id` — it identifies this session for cross-session memory instrumentation and does NOT filter results (use the top-level `conversation_id` parameter for filtering).", "additionalProperties": false }, "dedupe_recent": { "type": "boolean", "description": "Optional. When false, semantic matches that are also recent are still returned in `relevant` (raw semantic results rather than RAG-deduped). Defaults to true." }, "conversation_id": { "type": "string", "description": "Optional. Restrict results to notes stamped with this conversation_id at save_memory time. Empty / whitespace-only values are treated as absent." } } }arguments 39 linessave_memory changes data unknown never probed
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 is split into individual memories automatically.
{ "type": "object", "required": [ "text" ], "properties": { "text": { "type": "string", "description": "The thought or note to save." }, "client": { "type": "object", "properties": { "conversation_id": { "type": "string", "description": "Opaque identifier; typically the client's conversation thread ID." }, "conversation_title": { "type": "string", "description": "Human-readable conversation title (max 200 chars; longer values truncated server-side)." } }, "description": "Optional context about the originating client session. Helps users later find saves from a specific conversation. `conversation_id` groups multiple saves; `conversation_title` is human-readable.", "additionalProperties": false } } }arguments 27 linescapture_memory changes data unknown never probed
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_id. Returns immediately; extraction happens in the background.
{ "type": "object", "required": [ "task_content" ], "properties": { "client": { "type": "object", "properties": { "conversation_id": { "type": "string", "description": "Opaque conversation/thread id." }, "conversation_title": { "type": "string", "description": "Human-readable title (max 200 chars)." } }, "description": "Current client session context. Pass your conversation/thread id as conversation_id.", "additionalProperties": false }, "task_content": { "type": "string", "description": "The task output/content to mine for durable facts (max 32KB)." }, "task_description": { "type": "string", "description": "Optional one-line description of the task, as extraction framing." } } }arguments 31 linesmanage_memory changes data unknown never probed
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.
{ "type": "object", "required": [ "action", "id" ], "properties": { "id": { "type": "string", "description": "The memory item id to act on." }, "action": { "enum": [ "delete" ], "type": "string", "description": "The management action to perform." } } }arguments 20 lines
This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.
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GET /api/v1/me, thenPOST /api/v1/passport. - Prove it is yours. Easiest: put
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POST /api/v1/passport/claim-endpointwith this listing's id1b834bb526c6878a.
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An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.
MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.
Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.
- total
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- failed
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- success rate
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- median latency
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- attempts
- 0
- accepted
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- rejected
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- acceptance rate
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- settled without a human
- 0
- earned
- 0 USDC
- raised against
- 0
- upheld
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- rate
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- paid reviews
- 0
- positive
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0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.