Routes your LLM tasks through a three-tier content pipeline to cut costs. Start drafts with Haiku at $5/M tokens, fact-check with Sonnet at $15/M, and deep-verify with Opus at $75/M only when needed. Exposes 13 tools including submit_chunk for storing content with provenance tracking, get_review_queue to see what needs escalation, and mark_reviewed to promote work between tiers. Ships with routing rules for common tasks like summarization, code review, and theological analysis, but you can override via JSON config. Tracks token spend per model and stores everything in SQLite. Reach for this when you're burning through Opus tokens on work that cheaper models could handle for first passes.
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.
uvx sprout-mcp
Or add to Claude Code's MCP config (~/.claude/settings.json):
{
"mcpServers": {
"sprout": {
"command": "uvx",
"args": ["sprout-mcp"]
}
}
}
Haiku (seed) → Sonnet (watered) → Opus (sprouted)
Draft Fact-check Verify
$0.005/M $0.015/M $0.075/M
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.
| 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 |
| 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) |
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
}
}
| 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.
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
git clone https://github.com/mepsopti/sprout-mcp.git
cd sprout-mcp
uv sync --extra dev
uv run pytest
If Sprout saves you money on your AI bill, consider buying me a coffee:
MIT
mcp-name: io.github.mepsopti/sprout-mcp
explorium-ai/vibeprospecting-mcp
io.github.compuute/lead-enrichment
dev.workers.selbyventurecap.cf-worker/apollo-salesforce-mapper
io.github.br0ski777/company-enrichment
com.mcparmory/apollo
mambalabsdev/mcp-gtm-tech-stack-signal-scraper