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Minutes Conversation Memory

The private, owned conversation-memory layer for AI. Record, transcribe, and search every meeting, voice memo, and dictation entirely on your own machine — nothing uploaded — then let any AI you connect recall it. Plain-markdown output you keep forever; no cloud, no API key, no vendor to outlive.

Category
Productivity
View in the Claude registry
Integration details

Description

Minutes is the private, owned conversation-memory layer. Record meetings, voice memos, and dictation; transcribe them on your own machine; and get structured markdown in `~/meetings/` that policy-aware local tools expose to Claude Desktop, Claude Code, Codex, Gemini CLI, Cursor, OpenCode, Pi, and MCP-compatible clients — no proprietary SDK, no API key. Restricted meetings are excluded from agent results by default; explicit access requires a trusted launch policy, a per-call request, and a durable audit record. Minutes never uploads your audio; meeting text leaves your device only when you explicitly send policy-authorized context to a connected cloud agent or summarizer. When a cloud memory tool gets acquired or subpoenaed, your recordings aren't theirs to hand over. No vendor to outlive — ten years from now, `grep` still works on your corpus. 34 tools • 11 resources • Interactive MCP App dashboard • 6 prompt templates What you get: • On-device transcription with sealed local whisper.cpp and optional on-device summarization (Apple Foundation Models on macOS 26+) — your audio never leaves the machine. Retained Parakeet and Apple Speech preferences resolve to Whisper until those helpers support secure byte transport. • Re-run the AI pass on edited meetings and memos with preview-first output, backup-on-apply writes, and edit-preserving merges. • A native chat panel that recalls policy-authorized meetings, with token streaming and read-only policy-bound search. • Dictation that types straight at your cursor, on the same local engine. • Live sessions that promote into diarized, summarized meetings when you stop. • Consent provenance in every file, and sensitivity gating agents must respect. • Diarized speaker labels, structured action items and decisions, and policy-safe search over owned markdown. Cross-meeting relationship answers are rebuilt from bounded live policy-authorized snapshots; compatibility-only derived insight and annotation reads still fail explicitly until their source provenance can be revalidated. **Before you start.** Minutes runs entirely on your own machine, so it needs the Minutes engine installed locally. The extension normally downloads it for you the first time it runs. If your machine cannot reach the internet, or you are on a platform we do not publish a binary for, install it yourself: on macOS and Windows get the free desktop app from https://useminutes.app, which includes the engine and keeps it updated; on Linux install the CLI from the same page. Until the engine is present the extension still starts and lists its tools, and each tool will tell you what is missing.

Integration type
Connector
Verification status
Verified connector
Platform
Claude
Category
Productivity

The broad Category that contains the Primary Subcategory.

Primary Subcategory
Meeting Notes & Call Intelligence

The Primary Subcategory used for this profile’s headline score.

Secondary Subcategories
None listed

Other Subcategories where the Integration is listed.

Brand
Minutes
Access
Unknown
First tracked
2026-08-15
Tool count
34
Geography
US

Claude Discoverability Score

Minutes Conversation Memory isn’t discoverable through Claude’s Connector picker

It runs as a local Claude Desktop Extension, so Claude cannot surface or score it there today.

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What the current score measures

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How this score is measured
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Attention11/100
Minutes Conversation MemoryLocal Extension · Not scored
Recommended guideHow to get your Claude Connector organically discoveredFollow the practical steps agents use to find, shortlist, and choose your Connector.Read guide
Tools

34 tools agents can invoke

Minutes Conversation Memory FAQ
How do I improve a Verified connector's discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.