MCP server

Memoket Official

ai.memoket/memoket

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

Memoket — access your recording transcripts, summaries, and key takeaways over MCP.

Source

At a glance

Type

MCP server

Publisher

memoket.ai (verified by the MCP Registry)

Status

Working at last check

Tools

7

Token cost

About 1,482 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 memoket https://mcp.memoket.ai/mcp

Claude Desktop

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

Codex (config.toml)

[mcp_servers.memoket]
url = "https://mcp.memoket.ai/mcp"

Gemini CLI

{"mcpServers":{"memoket":{"httpUrl":"https://mcp.memoket.ai/mcp"}}}

Cursor

{"mcpServers":{"memoket":{"url":"https://mcp.memoket.ai/mcp"}}}

VS Code

{"servers":{"memoket":{"type":"http","url":"https://mcp.memoket.ai/mcp"}}}

Antigravity

agy mcp add memoket https://mcp.memoket.ai/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":"memoket","server_url":"https://mcp.memoket.ai/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"memoket","server_url":"https://mcp.memoket.ai/mcp"}

Tools

• get_brief ~151 tokens
  [content_fetch] Per-conversation compact report body for the given conversation_ids using Brief -> Summary -> Standard, where Standard is the first completed non-empty type=0 report.
• get_conversations ~117 tokens
  [metadata_query] Conversation-level metadata for the given conversation_ids: id, title, started_at, ended_at, duration_seconds, participants, language_code. No transcript, brief, or summary body.
• get_summaries ~176 tokens
  [content_fetch] Per-conversation summary body. With summary_ids, fetch exact summary reports from search_recordings. With conversation_ids only, fetch the latest summary report for each conversation. Paginated (offset).
• get_transcripts ~161 tokens
  [content_fetch] Verbatim transcript of ONE recording; at most 100 lines / 4000 characters per page. Resume using both next_offset and next_text_offset from the returned item, including within a long line.
• get_transcripts_by_participant ~165 tokens
  [content_fetch] Transcript lines associated with participant_ids in conversation_ids. Turns participant metadata into transcript evidence for exposed search results.
• list_conversations ~365 tokens
  [metadata_query] List recordings by time window / participants. Returns id, title, started_at, ended_at, duration_seconds, participants, language_code (no content). Paginated (count default 100, max 200; offset). order_by ranks within the window. NOTE: `participants` are speaker labels — placeholder
• search_recordings ~347 tokens
  [search] Unified recording search. Runs bounded searches over transcript lines, topic segments, memory atoms, participant metadata, titles, briefs, summaries, and action items in one call. Returns typed hits plus conversation_ids, line_ids, segment_ids, memory_atom_ids, participant_ids, brief_ids, s

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