Sprout MCP

Name: Sprout MCP
Author: mepsopti

by mepsoptiversion 0.1.4i★ –iRuns on your computer

Registry nameio.github.mepsopti/sprout-mcp

Install

Overview

Description from the maker (original English)

Model-tiered content pipeline — cheap models seed, expensive models verify

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

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": {
    "sprout": {
      "command": "uvx",
      "args": [
        "sprout-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add sprout -- uvx sprout-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "sprout": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "sprout-mcp"
      ]
    }
  }
}

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.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account mepsopti, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32718 servers in this category
Published to the registry more recently than 3% of the other 32718 servers in this category
Basic checks equal to or better than 100% of the other 32718 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Sprout MCP safe?

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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.4) reached the registry 8 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, MemberVault MCP by usefulapi

Alternatives

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README from the maker

Open the README

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.

Sprout MCP

Drop your Opus bill 80%. Model-tiered content pipeline for MCP — cheap models seed work, expensive models verify it.

Sprout routes tasks to the right model tier automatically. Haiku drafts, Sonnet fact-checks, Opus verifies. Every chunk tracks provenance, confidence, and cost.

Install

uvx sprout-mcp

Or add to Claude Code's MCP config (~/.claude/settings.json):

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

How It Works

  Haiku (seed)  →  Sonnet (watered)  →  Opus (sprouted)

Draft Fact-check Verify $0.005/M $0.015/M $0.075/M

Seed — Haiku drafts content cheaply (summarization, extraction, first passes)
Water — Sonnet reviews and fact-checks the seeds
Sprout — Opus deep-verifies only what passed Sonnet's review

Instead of running everything through Opus at $75/M output tokens, most work stays at Haiku's $5/M. Only the final verification — typically 10-20% of total work — touches Opus.

Tools (13)

Tool	Description
`submit_chunk`	Store content with provenance (model, task type, sources)
`get_review_queue`	List chunks needing review, filtered by confidence/project
`mark_reviewed`	Promote (seed→watered→sprouted) or reject chunks
`recommend_model`	Get model recommendation for a task type
`get_stats`	Dashboard of chunk counts, confidence levels, token usage
`export_chunks`	Export verified chunks as JSON
`opus_test`	Generate structured review summary for batch verification
`schedule_task`	Schedule tasks to run at a specific time or delay
`list_scheduled`	View pending scheduled tasks
`cancel_scheduled`	Cancel a pending scheduled task
`configure_routing`	Add/update routing rules at runtime
`get_cost_report`	Estimated spend per model with real pricing
`retry_on_error`	Track failed attempts with backoff guidance

Configuration

Environment Variables

Variable	Default	Description
`SPROUT_DB_PATH`	`~/.sprout/sprout.db`	SQLite database location
`SPROUT_CONFIG`	(none)	Path to JSON config file for custom routes and pricing
`SPROUT_MAX_RETRIES`	`3`	Max retry attempts before giving up
`SPROUT_RETRY_BACKOFF`	`2.0`	Exponential backoff base (seconds)

Custom Config File

Create a JSON file and point SPROUT_CONFIG at it:

"routes": { "code_review": { "tier": "sonnet", "reason": "Code analysis needs reasoning" }, "translation": { "tier": "haiku", "reason": "Straightforward language task" } }, "pricing": { "custom-model": 10.00 } }

Default Routing Table

Task Type	Tier	Why
`biography_synthesis`	haiku	Factual summarization
`council_description`	haiku	Historical summarization
`document_synopsis`	haiku	Content summarization
`json_validation`	haiku	Structural verification
`summarization`	haiku	General summarization
`data_extraction`	haiku	Structured extraction
`fact_check_first_pass`	sonnet	Cross-reference claims
`code_review`	sonnet	Code analysis
`fact_check_final`	opus	Deep factual verification
`theological_analysis`	opus	Domain expertise required
`complex_analysis`	opus	Deep reasoning required

Unknown task types default to haiku — start cheap, escalate if needed.

Example Workflow

You: Use recommend_model for "biography_synthesis"

Sprout: biography_synthesis → haiku-4.5 (Factual summarization)

You: Use submit_chunk to store the Haiku output Sprout: Stored chunk abc12345 [seed] for person-001.biography

You: Use get_review_queue to see what needs fact-checking Sprout: 1 chunk pending review

You: Use mark_reviewed to promote after Sonnet fact-checks it Sprout: Chunk abc12345 → watered (verified by sonnet-4.6)

You: Use get_cost_report Sprout: haiku-4.5: ~1,300 tokens (1 chunk) — $0.0065 Total: $0.0065

Development

git clone https://github.com/mepsopti/sprout-mcp.git

cd sprout-mcp uv sync --extra dev uv run pytest

Support

If Sprout saves you money on your AI bill, consider buying me a coffee:

License

MIT

mcp-name: io.github.mepsopti/sprout-mcp

Sprout MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

MemberVault MCP by usefulapi

README from the maker

Sprout MCP

Install

How It Works

Tools (13)

Configuration

Environment Variables

Custom Config File

Default Routing Table

Example Workflow

Development

Support

License