Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Description from the maker (original English)
Local MCP server for meeting transcripts, summaries, action items & decisions — no cloud.
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
SAMURAIZER_MEETINGS_DIRYou need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"samuraizer": {
"command": "npx",
"args": [
"-y",
"@samuraizer/mcp-server"
],
"env": {
"SAMURAIZER_MEETINGS_DIR": "your-value"
}
}
}
}Run this in your terminal
claude mcp add samuraizer --env SAMURAIZER_MEETINGS_DIR=your-value -- npx -y @samuraizer/mcp-serverFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"samuraizer": {
"command": "npx",
"args": [
"-y",
"@samuraizer/mcp-server"
],
"env": {
"SAMURAIZER_MEETINGS_DIR": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"samuraizer": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@samuraizer/mcp-server"
],
"env": {
"SAMURAIZER_MEETINGS_DIR": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
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SAMURAIZER_MEETINGS_DIR envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account UladzKha, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.7) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Agent-Native Google Calendar - manage events, sync, and public booking
Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Local-first MCP server that gives AI agents access to your meeting recordings — transcripts, summaries, action items, and decisions — without sending anything to the cloud.
Model Context Protocol server for Samuraizer — exposes processed meetings to AI agents (Claude Desktop, Claude Code, MCP Inspector, etc.) over stdio.
get_meeting for those. Returns ranked results with snippets.Full input and output details for each tool are in Tools below.
The server provides two modes:
samuraizer itself: whisper-cli, ffmpeg, ffprobe, and a running Ollama instance.Everything stays local. The server reads meetings from a directory on your machine and never sends data to any external service.
This package depends on @samuraizer/cli for its config and pipeline. Before using the MCP server, install and initialize the CLI:
npm install -g @samuraizer/cli
samuraizer init
Edit the generated config (path printed by samuraizer config path) and make sure meetingsDir points to the directory where your processed meetings live. The MCP server reads from that same directory.
For process mode, you additionally need the Samuraizer runtime dependencies installed and configured: whisper-cli from whisper.cpp, ffmpeg / ffprobe, and a running Ollama server with a pulled model. See the main Samuraizer README for setup details.
For query mode only (list_meetings, get_meeting, meeting:// resources), none of the runtime dependencies are required — just a populated meetingsDir.
npm install -g @samuraizer/mcp-server
This exposes a samuraizer-mcp binary on your PATH.
samuraizer-mcp
The server speaks MCP over stdio. It is not meant to be used interactively from a shell — it is intended to be launched by an MCP client such as Claude Desktop or MCP Inspector.
npx @modelcontextprotocol/inspector samuraizer-mcp
Opens a browser UI where you can list tools and resources, call them with arguments, and see responses. Useful for debugging.
Add the server to your Claude Desktop configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or ~/.config/Claude/claude_desktop_config.json (Linux)%APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": { "samuraizer": { "command": "samuraizer-mcp" } } }
If samuraizer-mcp is not found by Claude Desktop (PATH issues are common with version managers like fnm, nvm, or volta), use an absolute path instead. Find it with which samuraizer-mcp, then:
{
"mcpServers": { "samuraizer": { "command": "/absolute/path/to/samuraizer-mcp" } } }
You can also override the meetings directory per-server via environment variables:
{
"mcpServers": { "samuraizer-personal": { "command": "samuraizer-mcp", "env": { "SAMURAIZER_MEETINGS_DIR": "/Users/me/personal-meetings" } }, "samuraizer-work": { "command": "samuraizer-mcp", "env": { "SAMURAIZER_MEETINGS_DIR": "/Users/me/work-meetings" } } } }
Restart Claude Desktop after editing the config.
claude mcp add samuraizer samuraizer-mcp
See the Claude Code MCP documentation for managing MCP servers from the CLI.
The MCP server reads the same config file as @samuraizer/cli. There is no separate config for the server itself.
All config fields accept env-var overrides, useful for running the server in different contexts (e.g. one MCP server per project):
| Variable | Maps to |
|---|---|
SAMURAIZER_MEETINGS_DIR | meetingsDir |
SAMURAIZER_MODEL | model |
SAMURAIZER_OLLAMA_BASE_URL | ollamaBaseUrl |
SAMURAIZER_WHISPER_COMMAND | whisperCommand |
SAMURAIZER_WHISPER_MODEL_PATH | whisperModelPath |
SAMURAIZER_WHISPER_DEVICE | whisperDevice |
SAMURAIZER_WHISPER_PROMPT | whisperPrompt |
SAMURAIZER_WHISPER_CARRY_INITIAL_PROMPT | whisperCarryInitialPrompt |
SAMURAIZER_LANGUAGE | language |
SAMURAIZER_FFMPEG_COMMAND | ffmpegCommand |
SAMURAIZER_FFPROBE_COMMAND | ffprobeCommand |
SAMURAIZER_LLM_CONCURRENCY | llmConcurrency |
Env vars override values from the config file. Booleans accept 1/0, true/false, yes/no, or on/off.
llmConcurrency defaults to 1, so process_recording runs summary, action-item, and decision extraction sequentially on all hardware. Values 2 and 3 explicitly opt into parallel Ollama requests and require enough spare VRAM for additional KV-cache slots.
search_meetingsSearch processed meetings by summary text, meeting name, action items, and decisions.
Transcripts are deliberately not searched — they are one to two orders of magnitude larger than the fields above, and scanning them on every query would not scale. Use get_meeting when you need the transcript.
Input:
query *(string, required)* — search query, case-insensitive. See Query syntax.limit *(integer, optional)* — maximum results to return (default 10).Returns: JSON array of ranked results, each with id, name, generated_at, duration_sec, score, matched_in (any of summary, name, action_items, decisions), and a snippet around the best match. Results are ranked by how many fields matched — a summary hit weighs more than a name, action-item, or decision hit — with ties broken by recency. Useful for finding a specific meeting without enumerating all of them.
The query is split into words, and a meeting matches only when every word is found. The words do not have to share a field, so patient id post log matches a meeting whose summary mentions the patient ID and whose action items mention the post log.
Each word matches as a substring, so export finds exporter.
Wrap the query in double quotes to require an exact phrase instead:
patient id post log → all four words, anywhere in the searched fields
"patient id post log" → that exact run of characters, in one field
A meeting containing the whole query verbatim scores above one that merely scatters the same words, so exact matches still surface first.
list_meetingsList processed meetings, sorted newest first.
Input:
limit *(integer, optional)* — maximum number of results to return.Returns: JSON array of meeting summaries (id, name, generated_at, summary_preview, participant_count, duration_sec).
get_meetingRetrieve the full processed output for a specific meeting.
Input:
id *(string, required)* — the meeting ID (ULID).Returns: the full meeting JSON, including transcript, summary, action items, decisions, and provenance metadata. Returns an error if the meeting is not found.
These tools run parts of the Samuraizer pipeline on demand. They have local runtime dependencies (whisper-cli, ffmpeg, Ollama).
process_recordingRun the full pipeline on an audio file. Recommended entrypoint for processing recordings via an agent.
Input:
filePath *(string, required)* — absolute path to the audio file.model *(string, optional)* — Ollama model to use; falls back to the configured default.Returns: JSON with summary, action items, decisions, and output file paths.
normalize_audioNormalize an audio file to 16 kHz mono PCM WAV (the format Whisper expects).
Input: inputPath, outputPath (both required absolute paths).
transcribe_audioTranscribe an audio file with whisper.cpp.
Input: filePath (required absolute path).
summarize_transcriptGenerate a meeting summary from transcript text.
Input: transcriptText (required), model (optional).
extract_action_itemsExtract action items from a transcript.
Input: transcriptText (required), model (optional).
extract_decisionsExtract confirmed decisions from a transcript.
Input: transcriptText (required), model (optional).
The server exposes each processed meeting as an MCP resource:
meeting://{id}application/jsonget_meeting returns.Listing resources returns one entry per meeting in meetingsDir. Reading a resource returns its full content. Resources are particularly useful for clients that surface them in their UI (e.g. Claude Desktop's resource picker).
All meeting JSON conforms to the open Samuraizer meeting-output schema, which describes meeting structure, transcript segments, summaries, action items, decisions, and provenance metadata.
The schema and its specification live in the memnex-spec package:
spec/meeting-output.schema.jsonspec/SPEC.mdspec/examples/Error: The config file is not created, please run 'samuraizer init'The MCP server uses the same config as the CLI. Install @samuraizer/cli and run samuraizer init first.
list_meetings returns an empty arrayEither meetingsDir is empty, or all meeting.json files in it failed schema validation. The server logs structured warnings to stderr for each invalid meeting it skips — check the terminal where the MCP server is running (or the Claude Desktop logs at `~/Library/Logs/Claude/mcp-serv
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