Datoon

Smart structured-data to TOON gateway: converts to TOON only when it saves LLM tokens.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "datoon": {
      "command": "uvx",
      "args": [
        "pre-commit"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

datoon

smart structured-data→TOON gateway — converts only when it actually saves tokens

Before/After • Install • What You Get • How It Works • Benchmarks • Full install guide

Raw structured data is often verbose in LLM prompts. TOON can save tokens — but blind conversion can also make payloads worse. datoon adds a decision layer: convert when structure and savings justify it, skip when they don't, and always explain why.

Supports JSON, CSV, JSONL, YAML, XML, Parquet, Avro, ORC, Excel, and Apple Numbers — auto-detected from file extension.

Before / After

JSON in the prompt (43 tokens)

config.json

{"users":[
  {"id":1,"name":"Ada","role":"admin"},
  {"id":2,"name":"Lin","role":"analyst"},
  {"id":3,"name":"Grace","role":"viewer"}
]}

datoon converts → TOON (24 tokens)

toon

users[3]{id,name,role}:
  1,Ada,admin
  2,Lin,analyst
  3,Grace,viewer

config.json

{"decision":"convert","reason":"Estimated savings 44.19% (threshold 15.00%)."}

CSV from a data pipeline (111 tokens as JSON)

csv

id,name,role
1,Ada,admin
2,Lin,analyst
3,Grace,viewer

datoon auto-converts → TOON (24 tokens)

bash

datoon data.csv --report-stdout

Same result. Zero JSON serialization in your code.

Non-uniform payload (26 tokens)

config.json

{"config":{"debug":true},"tags":["a","b"]}

datoon skips → keeps JSON

config.json

{"decision":"skip","reason":"No uniform object arrays found with at least 3 rows."}

No Node.js call. No silent corruption.

Same data. Right format. Always explained.

Code

┌──────────────────────────────────────────────────┐
│  PAYLOAD SAVINGS (auto avg)    ████░░░░░░   28%  │
│  PAYLOAD SAVINGS (agent skill) ████████░░   62%  │
│  DECISION ACCURACY             ██████████  100%  │
│  HARMFUL CONVERSIONS BLOCKED   ██████████  100%  │
└──────────────────────────────────────────────────┘

[!IMPORTANT] datoon saves payload tokens — the structured data portion of your prompt. Token savings depend on payload shape: uniform tabular data converts well; deeply nested or non-uniform structures are skipped. Every decision includes a reason so pipelines can log, debug, and trust the outcome.

Install

bash

# core (JSON, CSV, JSONL, XML — no extra deps)
uv add datoon
pip install datoon

# with YAML support
pip install "datoon[yaml]"

# with Excel support
pip install "datoon[excel]"

# with Parquet / ORC / Avro support
pip install "datoon[columnar]"

# with Apple Numbers support
pip install "datoon[numbers]"

# with tiktoken-based token counting
pip install "datoon[tokens]"

# with MCP server
pip install "datoon[mcp]"

# everything
pip install "datoon[all]"

Requires Python 3.12+. TOON conversion requires Node.js with npx in PATH — analysis and format reading work without it.

For Claude Code plugin, Codex, and MCP config → INSTALL.md.

What You Get

	What
`datoon` CLI	Auto-gate any supported format → TOON from terminal or scripts
Python API	`convert_json_for_llm()` + `read_tabular()` for any LLM pipeline
MCP Server	`convert_json`, `convert_text`, `analyze_json` tools for Claude Desktop, Cursor, Windsurf
Claude Code Plugin	`/datoon` in-session trigger, installs from GitHub in one command
Codex Plugin	Marketplace plugin — structured-data mode for Codex

Supported input formats

Format	Extension	Extra needed
JSON	`.json`	—
JSONL	`.jsonl`, `.ndjson`	—
CSV	`.csv`	—
XML	`.xml`	—
YAML	`.yaml`, `.yml`	`datoon[yaml]`
Excel	`.xlsx`, `.xls`	`datoon[excel]`
Parquet	`.parquet`	`datoon[columnar]`
Avro	`.avro`	`datoon[columnar]`
ORC	`.orc`	`datoon[columnar]`
Apple Numbers	`.numbers`	`datoon[numbers]`

How It Works

Detect format — from --format flag, file extension, or default to JSON for stdin
Read + normalize — parse source into list of row dicts; serialize to compact JSON
Analyze structure — uniform object arrays? acceptable depth? minimum rows?
Gate early — non-candidates skip before any CLI call; no Node.js overhead
Convert + estimate — TOON CLI runs, token savings calculated
Gate savings — below threshold → return JSON; above → return TOON with report

Every path returns a ConversionReport with decision, reason, and token estimates. Pipelines never get silent surprises.

Quick Start

JSON (stdin):

bash

echo '{"users":[{"id":1,"name":"Ada"},{"id":2,"name":"Lin"},{"id":3,"name":"Grace"}]}' | datoon --report-stdout

CSV (auto-detected from extension):

bash

datoon data.csv --report-stdout

JSONL:

bash

datoon data.jsonl -o output.toon

YAML (requires datoon[yaml]):

bash

datoon data.yaml --report-stdout

Parquet (requires datoon[columnar]):

bash

datoon data.parquet --report ./report.json

Explicit format override:

bash

datoon --format csv < data.csv --report-stdout

Force conversion (bypass gating — for experiments):

bash

datoon data.json --force --report-stdout

Python API

JSON conversion:

server.ts

from datoon import convert_json_for_llm, ConversionConfig, DatoonError

config = ConversionConfig(min_savings_ratio=0.15, max_depth=6, min_uniform_rows=3)

try:
    outcome = convert_json_for_llm(raw_json, config)
except DatoonError as exc:
    raise

# outcome.payload_text  — TOON or original JSON
# outcome.report.decision  — "convert" | "skip"
# outcome.report.reason    — human-readable explanation
send_to_model(outcome.payload_text)

Any format via read_tabular:

server.ts

import json
from pathlib import Path
from datoon import read_tabular, convert_json_for_llm, ConversionConfig

# text formats: csv, jsonl, yaml, xml
rows = read_tabular("csv", text=csv_string)

# binary formats: excel, parquet, orc, avro, numbers
rows = read_tabular("parquet", path=Path("data.parquet"))

json_text = json.dumps(rows, separators=(",", ":"))
outcome = convert_json_for_llm(json_text, ConversionConfig())
send_to_model(outcome.payload_text)

Structure-only analysis (no Node.js required):

server.ts

from datoon.analyzer import analyze_payload
from datoon.models import ConversionConfig

analysis = analyze_payload(parsed_data, ConversionConfig())
print(analysis.is_candidate, analysis.reason)

MCP Server

datoon ships an MCP server with three tools:

Tool	Description
`convert_json`	Full JSON conversion with policy gating
`convert_text`	Converts CSV, YAML, XML, or JSONL text with policy gating
`analyze_json`	Structure analysis only — no Node.js needed

Claude Desktop / Cursor / Windsurf config:

config.json

{
  "mcpServers": {
    "datoon": {
      "command": "uvx",
      "args": ["--from", "datoon[mcp]", "datoon", "mcp"]
    }
  }
}

Run locally:

bash

datoon mcp     # or the standalone script: datoon-mcp

Listed on the MCP Registry, Smithery, and Glama. See MARKETPLACES.md.

Claude Code Plugin

Install directly from GitHub:

Terminal

claude plugin marketplace add andrii-su/datoon
claude plugin install datoon@datoon

Trigger in-session:

Code

/datoon
convert this JSON to TOON if it saves tokens
use datoon mode for structured data

CLI Reference

Read the full README →View source on GitHub →

Related MCP Servers

View all in Cloud Platforms View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

npm downloads

1.6M

Package downloads in the last 30 days.

Last commit

25d ago

Most recent push to the default branch.

Directory activity

1 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Datoon

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "datoon": { "command": "uvx", "args": ["pre-commit"] } }

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Technical Specs & Signals

CategoryCloud Platforms

3/7 checks healthy over the last 47d

45Quality signal: Fair · 45/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools16/30

Adoption & activity8/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 7d ago via OSV.dev · pre-commit (PyPI)

★ Featured

Moxie Docs MCP

MCP & Agent Skills for Automated Documentation, and codebase conventions + context

Explore Server →

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More in ☁️ Cloud Platforms →Best MCP servers for Cloud Platforms →Alternatives to Datoon →Install in Claude Desktop Install in Cursor Install in VS Code Setup guides for all 13 MCP clients

Datoon

Smart structured-data to TOON gateway: converts to TOON only when it saves LLM tokens.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "datoon": {
      "command": "uvx",
      "args": [
        "pre-commit"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

datoon

smart structured-data→TOON gateway — converts only when it actually saves tokens

Before/After • Install • What You Get • How It Works • Benchmarks • Full install guide

Supports JSON, CSV, JSONL, YAML, XML, Parquet, Avro, ORC, Excel, and Apple Numbers — auto-detected from file extension.

Before / After

JSON in the prompt (43 tokens)

config.json

{"users":[
  {"id":1,"name":"Ada","role":"admin"},
  {"id":2,"name":"Lin","role":"analyst"},
  {"id":3,"name":"Grace","role":"viewer"}
]}

datoon converts → TOON (24 tokens)

toon

users[3]{id,name,role}:
  1,Ada,admin
  2,Lin,analyst
  3,Grace,viewer

config.json

{"decision":"convert","reason":"Estimated savings 44.19% (threshold 15.00%)."}

CSV from a data pipeline (111 tokens as JSON)

csv

id,name,role
1,Ada,admin
2,Lin,analyst
3,Grace,viewer

datoon auto-converts → TOON (24 tokens)

bash

datoon data.csv --report-stdout

Same result. Zero JSON serialization in your code.

Non-uniform payload (26 tokens)

config.json

{"config":{"debug":true},"tags":["a","b"]}

datoon skips → keeps JSON

config.json

{"decision":"skip","reason":"No uniform object arrays found with at least 3 rows."}

No Node.js call. No silent corruption.

Same data. Right format. Always explained.

Code

┌──────────────────────────────────────────────────┐
│  PAYLOAD SAVINGS (auto avg)    ████░░░░░░   28%  │
│  PAYLOAD SAVINGS (agent skill) ████████░░   62%  │
│  DECISION ACCURACY             ██████████  100%  │
│  HARMFUL CONVERSIONS BLOCKED   ██████████  100%  │
└──────────────────────────────────────────────────┘

[!IMPORTANT] datoon saves payload tokens — the structured data portion of your prompt. Token savings depend on payload shape: uniform tabular data converts well; deeply nested or non-uniform structures are skipped. Every decision includes a reason so pipelines can log, debug, and trust the outcome.

Install

bash

# core (JSON, CSV, JSONL, XML — no extra deps)
uv add datoon
pip install datoon

# with YAML support
pip install "datoon[yaml]"

# with Excel support
pip install "datoon[excel]"

# with Parquet / ORC / Avro support
pip install "datoon[columnar]"

# with Apple Numbers support
pip install "datoon[numbers]"

# with tiktoken-based token counting
pip install "datoon[tokens]"

# with MCP server
pip install "datoon[mcp]"

# everything
pip install "datoon[all]"

Requires Python 3.12+. TOON conversion requires Node.js with npx in PATH — analysis and format reading work without it.

For Claude Code plugin, Codex, and MCP config → INSTALL.md.

What You Get

	What
`datoon` CLI	Auto-gate any supported format → TOON from terminal or scripts
Python API	`convert_json_for_llm()` + `read_tabular()` for any LLM pipeline
MCP Server	`convert_json`, `convert_text`, `analyze_json` tools for Claude Desktop, Cursor, Windsurf
Claude Code Plugin	`/datoon` in-session trigger, installs from GitHub in one command
Codex Plugin	Marketplace plugin — structured-data mode for Codex

Supported input formats

Format	Extension	Extra needed
JSON	`.json`	—
JSONL	`.jsonl`, `.ndjson`	—
CSV	`.csv`	—
XML	`.xml`	—
YAML	`.yaml`, `.yml`	`datoon[yaml]`
Excel	`.xlsx`, `.xls`	`datoon[excel]`
Parquet	`.parquet`	`datoon[columnar]`
Avro	`.avro`	`datoon[columnar]`
ORC	`.orc`	`datoon[columnar]`
Apple Numbers	`.numbers`	`datoon[numbers]`

How It Works

Detect format — from --format flag, file extension, or default to JSON for stdin
Read + normalize — parse source into list of row dicts; serialize to compact JSON
Analyze structure — uniform object arrays? acceptable depth? minimum rows?
Gate early — non-candidates skip before any CLI call; no Node.js overhead
Convert + estimate — TOON CLI runs, token savings calculated
Gate savings — below threshold → return JSON; above → return TOON with report

Every path returns a ConversionReport with decision, reason, and token estimates. Pipelines never get silent surprises.

Quick Start

JSON (stdin):

bash

echo '{"users":[{"id":1,"name":"Ada"},{"id":2,"name":"Lin"},{"id":3,"name":"Grace"}]}' | datoon --report-stdout

CSV (auto-detected from extension):

bash

datoon data.csv --report-stdout

JSONL:

bash

datoon data.jsonl -o output.toon

YAML (requires datoon[yaml]):

bash

datoon data.yaml --report-stdout

Parquet (requires datoon[columnar]):

bash

datoon data.parquet --report ./report.json

Explicit format override:

bash

datoon --format csv < data.csv --report-stdout

Force conversion (bypass gating — for experiments):

bash

datoon data.json --force --report-stdout

Python API

JSON conversion:

server.ts

from datoon import convert_json_for_llm, ConversionConfig, DatoonError

config = ConversionConfig(min_savings_ratio=0.15, max_depth=6, min_uniform_rows=3)

try:
    outcome = convert_json_for_llm(raw_json, config)
except DatoonError as exc:
    raise

# outcome.payload_text  — TOON or original JSON
# outcome.report.decision  — "convert" | "skip"
# outcome.report.reason    — human-readable explanation
send_to_model(outcome.payload_text)

Any format via read_tabular:

server.ts

import json
from pathlib import Path
from datoon import read_tabular, convert_json_for_llm, ConversionConfig

# text formats: csv, jsonl, yaml, xml
rows = read_tabular("csv", text=csv_string)

# binary formats: excel, parquet, orc, avro, numbers
rows = read_tabular("parquet", path=Path("data.parquet"))

json_text = json.dumps(rows, separators=(",", ":"))
outcome = convert_json_for_llm(json_text, ConversionConfig())
send_to_model(outcome.payload_text)

Structure-only analysis (no Node.js required):

server.ts

from datoon.analyzer import analyze_payload
from datoon.models import ConversionConfig

analysis = analyze_payload(parsed_data, ConversionConfig())
print(analysis.is_candidate, analysis.reason)

MCP Server

datoon ships an MCP server with three tools:

Tool	Description
`convert_json`	Full JSON conversion with policy gating
`convert_text`	Converts CSV, YAML, XML, or JSONL text with policy gating
`analyze_json`	Structure analysis only — no Node.js needed

Claude Desktop / Cursor / Windsurf config:

config.json

{
  "mcpServers": {
    "datoon": {
      "command": "uvx",
      "args": ["--from", "datoon[mcp]", "datoon", "mcp"]
    }
  }
}

Run locally:

bash

datoon mcp     # or the standalone script: datoon-mcp

Listed on the MCP Registry, Smithery, and Glama. See MARKETPLACES.md.

Claude Code Plugin

Install directly from GitHub:

Terminal

claude plugin marketplace add andrii-su/datoon
claude plugin install datoon@datoon

Trigger in-session:

Code

/datoon
convert this JSON to TOON if it saves tokens
use datoon mode for structured data

CLI Reference

Read the full README →View source on GitHub →

Related MCP Servers

View all in Cloud Platforms View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

npm downloads

1.6M

Package downloads in the last 30 days.

Last commit

25d ago

Most recent push to the default branch.

Directory activity

1 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Datoon

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "datoon": { "command": "uvx", "args": ["pre-commit"] } }

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:

Live Dynamic SVG Preview

Markdown (GitHub README)

[![AllMCPs](https://allmcps.com/api/badge/datoon?style=directory)](https://allmcps.com/mcp/datoon)

HTML Embed

<a href="https://allmcps.com/mcp/datoon"><img src="https://allmcps.com/api/badge/datoon?style=directory" alt="Datoon on AllMCPs" /></a>

Technical Specs & Signals

CategoryCloud Platforms

3/7 checks healthy over the last 47d

45Quality signal: Fair · 45/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools16/30

Adoption & activity8/15

Community engagement0/10

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 7d ago via OSV.dev · pre-commit (PyPI)

★ Featured

Moxie Docs MCP

MCP & Agent Skills for Automated Documentation, and codebase conventions + context

Explore Server →

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

Explore more

More in ☁️ Cloud Platforms →Best MCP servers for Cloud Platforms →Alternatives to Datoon →Install in Claude Desktop Install in Cursor Install in VS Code Setup guides for all 13 MCP clients