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Sprout MCP

Official registry Security

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

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

PYPI package sprout-mcp
Claude Code 
claude mcp add sprout-mcp -- uvx sprout-mcp==0.1.4
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "sprout-mcp": {
            "command": "uvx",
            "args": [
                "sprout-mcp==0.1.4"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Sprout MCP
  2. Install
  3. How It Works
  4. Tools (13)
  5. Configuration
  6. Example Workflow
  7. Development
  8. Support
  9. License

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
  1. Seed — Haiku drafts content cheaply (summarization, extraction, first passes)
  2. Water — Sonnet reviews and fact-checks the seeds
  3. 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)

ToolDescription
submit_chunkStore content with provenance (model, task type, sources)
get_review_queueList chunks needing review, filtered by confidence/project
mark_reviewedPromote (seed→watered→sprouted) or reject chunks
recommend_modelGet model recommendation for a task type
get_statsDashboard of chunk counts, confidence levels, token usage
export_chunksExport verified chunks as JSON
opus_testGenerate structured review summary for batch verification
schedule_taskSchedule tasks to run at a specific time or delay
list_scheduledView pending scheduled tasks
cancel_scheduledCancel a pending scheduled task
configure_routingAdd/update routing rules at runtime
get_cost_reportEstimated spend per model with real pricing
retry_on_errorTrack failed attempts with backoff guidance

Configuration

Environment Variables
VariableDefaultDescription
SPROUT_DB_PATH~/.sprout/sprout.dbSQLite database location
SPROUT_CONFIG(none)Path to JSON config file for custom routes and pricing
SPROUT_MAX_RETRIES3Max retry attempts before giving up
SPROUT_RETRY_BACKOFF2.0Exponential 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 TypeTierWhy
biography_synthesishaikuFactual summarization
council_descriptionhaikuHistorical summarization
document_synopsishaikuContent summarization
json_validationhaikuStructural verification
summarizationhaikuGeneral summarization
data_extractionhaikuStructured extraction
fact_check_first_passsonnetCross-reference claims
code_reviewsonnetCode analysis
fact_check_finalopusDeep factual verification
theological_analysisopusDomain expertise required
complex_analysisopusDeep 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

Frequently asked questions

What is Sprout MCP?

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

How do I install Sprout MCP?

It runs on your machine. In Claude Code: claude mcp add sprout-mcp -- uvx sprout-mcp==0.1.4. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Sprout MCP need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is Sprout MCP open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains Sprout MCP?

It is published by mepsopti. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.