asistonto-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@asistonto-mcp Create a question pack from these meeting notes about the label rollout."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
asistonto-mcp
An MCP server that teaches any AI assistant to build question packs for asistonto, a live meeting copilot.
asistonto listens to a meeting and, the moment a question it was told to watch for is actually being discussed, it surfaces that question. What it watches is a pack. Writing a good one used to be expert work: the questions have to be stated in a particular four-part format, and each of those parts belongs in a different field because of what was measured about retrieval — get that wrong and the pack loads fine and then stays dark all meeting.
This server hands that expertise to Claude, ChatGPT, Claude Code, Codex, or anything else that speaks MCP. You paste your meeting notes; the assistant writes the pack; the pack uploads to asistonto unchanged.
Install
There is nothing to install by hand. Every client below runs the server through
uvx, which fetches and launches it on demand. You need
uv and Python 3.12+.
The package is not on PyPI yet, so uvx asistonto-mcp will not find it.
Install it from the repository instead — this is the working command, and it is
the one used in every block below:
uvx --from git+https://github.com/R0DR0X/asistonto-mcp asistonto-mcpThat runs the server on stdio and waits, which is what an MCP client wants and
what looks like a hang in a terminal. Ctrl-C to leave. When PyPI publishing
happens the plain uvx asistonto-mcp will start working and every block here
gets shorter by three words; until then, use the --from form.
Claude Code
claude mcp add asistonto -- uvx --from git+https://github.com/R0DR0X/asistonto-mcp asistonto-mcpOr, for every project on this machine rather than one:
claude mcp add --scope user asistonto -- uvx --from git+https://github.com/R0DR0X/asistonto-mcp asistonto-mcpCheck it with claude mcp list; the line should end in ✔ Connected. To upload
packs you also need an API token — see Getting a pack into
asistonto — which you can hand to the server at
registration time:
claude mcp add asistonto --env ASISTONTO_API_TOKEN=asist_... -- uvx --from git+https://github.com/R0DR0X/asistonto-mcp asistonto-mcpClaude Desktop
claude_desktop_config.json — macOS:
~/Library/Application Support/Claude/claude_desktop_config.json, Windows:
%APPDATA%\Claude\claude_desktop_config.json.
{
"mcpServers": {
"asistonto": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/R0DR0X/asistonto-mcp",
"asistonto-mcp"
],
"env": { "ASISTONTO_API_TOKEN": "asist_..." }
}
}
}Restart Claude Desktop afterwards. A desktop app has no shell to export a
variable in, so the token goes in env — which makes that config file a file
holding a secret. Keep it as private as the token itself, and leave env out
entirely if you only want to author packs and not upload them.
Cursor, Windsurf, and anything else taking the generic block
The same mcpServers object, in whichever file that client reads
(.cursor/mcp.json, ~/.codeium/windsurf/mcp_config.json, …):
{
"mcpServers": {
"asistonto": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/R0DR0X/asistonto-mcp",
"asistonto-mcp"
],
"env": {}
}
}
}Codex
Codex keeps its configuration in ~/.codex/config.toml — TOML, not JSON:
[mcp_servers.asistonto]
command = "uvx"
args = ["--from", "git+https://github.com/R0DR0X/asistonto-mcp", "asistonto-mcp"]
[mcp_servers.asistonto.env]
ASISTONTO_API_TOKEN = "asist_..."From a checkout
git clone https://github.com/R0DR0X/asistonto-mcp.git
uvx --from ./asistonto-mcp asistonto-mcpRelated MCP server: personal-meeting
What it gives the assistant
Tools
tool | what it does |
| the guidance below, for clients that cannot read resources |
| assembles one question from the four parts, each into the right field |
| reads an existing corpus document, in either format asistonto uses |
| lints phrasings: too few, keywords, document vocabulary, sibling collisions |
| everything that would fail to load, plus everything that would fail silently |
| writes |
| loads an existing pack the way the live server does, and validates it |
| sends a pack to asistonto over HTTP, so a session can pick it |
| writes the questions back out as markdown a person can correct |
| how many questions a pack needs before anything in it can fire |
Prompts — build_pack_for_meeting, write_paraphrases,
formulate_question, review_pack.
Resources — asistonto://guide/pack-format,
asistonto://guide/four-part-questions, asistonto://guide/paraphrases,
asistonto://guide/calibration, asistonto://guide/workflow,
asistonto://guide/publishing, asistonto://guide/labels,
asistonto://example/pack, asistonto://schema/brief.json.
The resources matter as much as the tools. An assistant that reads the paraphrase guidance before writing phrasings produces a materially better pack than one that only calls functions — the quality lives in judgement, and the judgement is written down there.
Worked example, end to end
1. Ask. In any client with the server registered:
Build me an asistonto pack for Tuesday's meeting with the warehouse lead about the new label. Here are my notes: (paste). The spec says the label carries the lot code, but the picking screen we saw last week only shows the pallet id, and nobody has said which one the scanner reads.
2. The assistant states each question in four parts and calls
compose_question:
part | content |
1 — where it came from |
|
2 — what was observed | the picking screen shown on 12 May displays only the pallet id |
3 — the question | when the operator scans at picking, does the code identify the pallet or the lot? |
4 — why it matters | the traceability chain hangs off which one is scanned |
which becomes one entry of brief.json:
{
"id": "QC-7",
"title": "what the scanner reads at picking",
"priority": "alta",
"source": "ETIQUETAS_v3.md",
"line": 41,
"probes": ["When the operator scans at picking, does the code identify the pallet or the lot?"],
"people": ["warehouse lead"],
"rationale": "the traceability chain hangs off which of the two is scanned",
"blocking": true,
"context": "ETIQUETAS_v3.md line 41 says the label carries the lot code. The picking screen shown on 12 May displays only the pallet id."
}The provenance sits in context, which is never indexed — indexing it costs
15 points of recall@1. The question sits in probes, the label in title, and
both of those are indexed.
3. Ten paraphrases per question, written from the question alone:
{
"QC-7": [
"when they scan at picking, what are they actually reading",
"the guy with the gun scans the pallet or the box",
"does the scan tell you which lot it is or just where it is",
"if two lots sit on the same pallet, how does the scan tell them apart",
"what comes up on the screen after the beep",
"can you tell from the scan which batch went out",
"is the code on the label the same one the system stores",
"do they scan once per pallet or once per unit",
"what happens when the label is torn and it does not scan",
"who decided which code goes on that label"
]
}4. validate_pack, then write_pack. You get a directory:
packs/almacen/
├── brief.json ← the only file the live loop reads
├── paraphrases.json ← the editable source, folded into the brief
└── background.txt ← a PAST meeting, for calibrationwrite_pack refuses two things outright: a pack that would not load, and a pack
too small for anything in it to ever fire. The second refusal is the important
one, because that pack loads perfectly and then does nothing (see the three
things worth knowing).
5. upload_pack, which puts it where the copilot can see it. That is the
next section.
Getting a pack into asistonto
A pack on your disk is not a pack asistonto can use. The copilot runs on a
server; the pack has to be sent there over HTTP. That is what upload_pack
does.
Once, per person
Get an account. Sign in at https://asistonto.escorpia.com. Sign-in goes through Google, so you need a Google account and you need to be able to reach the panel before any of this works.
Create an API token in the panel. It looks like
asist_…and it is shown once — copy it then, not later.Put it in the environment the MCP server runs in, as
ASISTONTO_API_TOKEN. From a shell:export ASISTONTO_API_TOKEN=asist_...For a GUI client, use the
envblock shown in its section above.
Running your own asistonto?
Set ASISTONTO_BASE_URL to your instance and everything below points at it
instead. That is necessary and not sufficient: POST /packs/<name> is only
registered when your instance has sign-in configured, and sign-in there is
all-or-nothing. Your server needs all four of
ASISTONTO_PUBLIC_ORIGIN=https://asistonto.example.com
ASISTONTO_OAUTH_CLIENT_ID=...
ASISTONTO_OAUTH_CLIENT_SECRET=...
ASISTONTO_OAUTH_DISCOVERY_URL=https://accounts.google.com/.well-known/openid-configurationplus ASISTONTO_ALLOWED_ACCOUNTS listing the e-mail addresses allowed to sign
in — with any one of the four missing, the whole account system is off, there is
no panel to make a token in, and the upload route does not exist. Uploading to
such an instance answers upload_not_available (a bare 404 from the server).
Your instance also decides how large a body it accepts; the default is 4 MiB.
The server reads the token from the environment and from nowhere else. It is never a tool argument — a tool argument is written into the transcript — and the server never writes it to a file. Do not paste it into a chat.
Per pack
Ask the assistant to upload it, or let it call the tool directly:
upload_pack(directory="packs/almacen")It sends brief.json, paraphrases.json and background.txt to
POST /packs/<name>. The account that uploads a pack owns it.
Then start the meeting
Open https://asistonto.escorpia.com, start a session, and pick the pack by name. Pack names must be letters, digits, dot, dash or underscore, starting with a letter or digit — the server rejects anything else.
When it does not work
what comes back | what happened | what to do |
|
| export it, or put it in the client's |
| the token is wrong, expired or revoked | create a new one in the panel and set it again |
| the name is taken on that instance; the message repeats the server's own reason — another account owns it, or an unclaimed pack directory already has that name | choose another name: |
| the pack is malformed; the message names the question | fix that question, |
| the pack is under the size floor and would stay dark | add questions until there are at least 25 |
| the body is over the instance's cap (4 MiB by default) | shorten |
| the instance hung up while the body was being sent — almost always the same size cap, answered too late to arrive | same as |
| that instance has no upload route: a self-hosted asistonto without the four OAuth variables set | |
| no network, or the wrong | check both |
The three things worth knowing before you start
Provenance is never a paraphrase. Parts 1 and 2 describe documents; paraphrases describe speech. Measured with paraphrases already indexed, adding the provenance took recall@1 from 71.1% down to 55.6%. Worse, writing paraphrases while reading the provenance pulls document vocabulary — codes, annex numbers, file names — into phrasings that nobody ever says.
Paraphrases must separate siblings, not reword them. Six ways of saying the
same thing all resemble the neighbouring question equally, and 70% of measured
top-1 errors landed on a sibling of the same block. check_paraphrases flags
phrasings that fit the neighbour better than their own question.
A small pack cannot fire at all. The live gate is a z-score over the pack's
own scores, so its ceiling is (n-1)/√n. Against the default gate of 4.75 that
means at least 25 questions — below it the panel stays dark all meeting and
looks exactly like a quiet room. This is why write_pack and upload_pack
refuse a pack that small instead of warning about it.
The measurements behind all of this are in the guide resources, which the assistant can read directly.
Development
git clone https://github.com/R0DR0X/asistonto-mcp.git
cd asistonto-mcp
uv venv && uv pip install -e '.[dev]'
uv run pytestThe test suite runs the MCP server over a real client session and asserts that
what it writes round-trips through a copy of the product's own loader
(tests/test_product_compatibility.py). It never opens a socket: the upload
tests replace upload.post_json, the one function in the package that would.
License
MIT.
Available Tools
9 toolscheck_paraphrasesA
Lint the paraphrases of one question before they go into a pack: count against the measured curve, phrasings that borrow document vocabulary from the provenance, phrasings that fit a sibling question better, duplicates and keywords.
Inputs: question (required), paraphrases (required), siblings. Returns: object
compose_questionA
Assemble one pack question from the four parts, placing each where the retrieval measurements say it belongs: the heading label and the question are indexed, the provenance and the stakes are not. Returns the question object plus what is still missing from it.
Inputs: id (required), title (required), question (required), line, +7 more. Returns: object
pack_authoring_guideA
Read the pack-authoring guidance. Same text as the asistonto:// resources, for clients that cannot read resources. Topics: pack-format, four-part-questions, paraphrases, calibration, workflow, labels, example, all.
Inputs: topic. Returns: result
pack_size_floorA
How many questions a pack needs before anything in it can fire, for a given gate. The live gate is a z-score over the pack's own scores, so a small pack has a ceiling below it and stays dark.
Inputs: z_threshold. Returns: object
parse_meeting_notesA
Parse a corpus document into pack questions. Accepts both shapes the asistonto corpus uses: the four-part blockquote format and the older ### QC-1 <title> headings with numbered sub-questions. Reports which one it read.
Inputs: markdown (required), prefix, source. Returns: object
read_packB
Read a pack from disk the way the live server does, and validate it. Use this to review or extend a pack that already exists.
Inputs: directory (required). Returns: object
render_question_documentA
Render questions back into the four-part markdown a person can read and correct. Keep it next to the pack: the pack is for the machine, this is for the room.
Inputs: questions (required). Returns: result
validate_packA
Validate a pack against the schema the live copilot loads, and against what measurement says will under-perform silently. Errors mean it will not load; warnings mean it will load and then quietly do less than it should.
Inputs: pack (required), questions (required), labels, background, +2 more. Returns: object
write_packB
Write a pack to a directory: brief.json, paraphrases.json and optionally background.txt and labels.json. Validates first and refuses to write a pack that would fail to load.
Inputs: pack (required), directory (required), questions (required), fuente, +5 more. Returns: object
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 9 tools
Most tools have clearly distinct purposes: parsing notes, composing questions, checking paraphrases, validating packs, rendering documents, and reading/writing packs all target different stages. The only minor overlap is between validate_pack and read_pack, since read_pack also validates, but the descriptions make the distinction clear.
The majority of tools follow a verb_noun pattern (compose_question, parse_meeting_notes, validate_pack, write_pack, read_pack), but two exceptions break the convention: pack_authoring_guide and pack_size_floor are noun phrases with no verb. This mixed pattern is readable but not fully consistent.
With 9 tools, the server is well-scoped for its purpose. Each tool covers a distinct step in the pack authoring workflow, and there is no obvious redundancy or bloat.
The tool set covers the full authoring lifecycle: guidance, parsing, composing, paraphrasing, validation, rendering, writing, reading, and sizing. Minor gaps exist (no explicit delete or update operation, no batch listing), but write_pack can overwrite packs and the core workflow is complete.
Maintenance
Related MCP Connectors
Bring meeting decisions, tasks and user stories into your AI editor (Claude, Cursor, Copilot).
Let AI assistants record meetings and work with notes, transcripts, contacts, and Drive.
Turn any recording or document into notes, flashcards and quizzes your agent can read and act on
Create, edit, translate, and export SCORM eLearning modules from a connected AI assistant.
Related MCP Servers
AlicenseNot gradedqualityBmaintenanceEnables AI assistants to search and retrieve meeting notes, summaries, and transcripts from note1, with tools to export markdown, check recording status, and manage meeting recordings.308 npm1MIT- AlicenseAqualityCmaintenanceEnables creating meeting minutes from unstructured meeting memos with validation, grounding checks, and user-approved saving.11MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to search meeting transcripts, retrieve speaker-attributed quotes, decisions, and action items, and transcribe new files or links directly from the QuillHub archive.MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to read, search, create, edit, move, and version Markdown notes, folders, tags, tasks, and attachments. It also supports generating meeting reports and bulk-importing notes through authenticated MCP connections.MIT