MCP server

Gnosem Official

dev.gnosem/gnosem

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Cross-vendor AI memory over MCP. One semantic store, readable and writeable from every MCP client.

Website Source

At a glance

Type

MCP server

Publisher

gnosem.dev (verified by the MCP Registry)

Status

Working at last check

Tools

6

Token cost

About 1,920 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http gnosem https://gnosem.dev/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.gnosem]
url = "https://gnosem.dev/mcp"

Gemini CLI

{"mcpServers":{"gnosem":{"httpUrl":"https://gnosem.dev/mcp"}}}

Cursor

{"mcpServers":{"gnosem":{"url":"https://gnosem.dev/mcp"}}}

VS Code

{"servers":{"gnosem":{"type":"http","url":"https://gnosem.dev/mcp"}}}

Antigravity

agy mcp add gnosem https://gnosem.dev/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"gnosem","server_url":"https://gnosem.dev/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"gnosem","server_url":"https://gnosem.dev/mcp"}

Tools

• memory_forget ~86 tokens
  Soft-delete a memory by id. The row is retained for audit but excluded from search/list and removed from the vector index.
• memory_list ~371 tokens
  List the user's most recent memories in reverse chronological order. Use for browsing or catching up on what the user's other model sessions have written recently. Same content/content_raw shape as memory_search. Optional filters (tags, written_by, session_id, since, until) narrow the listing at the
• memory_search ~480 tokens
  Search the user's memories. Default mode is 'hybrid': blends semantic (cosine over Vectorize) and keyword (BM25 over SQLite FTS5) hits via Reciprocal Rank Fusion (k=60). Semantic catches paraphrases; keyword catches exact-string hits (IDs, dates, code snippets). Pass mode:'semantic' or mode:'keyword
• memory_supersede ~176 tokens
  Replace a stale memory with a corrected one. The old row is marked superseded and excluded from future reads; the new row becomes the current version. Use for corrections; use memory_forget for pure deletions.
• memory_write ~448 tokens
  Save a fact, preference, decision, or note to the user's cross-model memory. Any MCP client can read this back later. Include written_by (e.g. 'claude-code', 'gpt-5', 'kimi-k2') for provenance and session_id to group related writes. Long content (>400 chars) is automatically compressed on write to a
• memory_write_bulk ~359 tokens
  Write up to 50 memories in a single call. Each entry runs the same path as memory_write (semantic dedup by default; pass force:true per-entry to skip). Embeddings + optimizations run in parallel; D1 inserts are batched. Returns { results: [...] } with one entry per input in the same order — each is

Browse

• Claude tools
• Databases
• Searching your documents (RAG)
• Calling other AI models

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