“I want a small open-source MCP retrieval router that defaults to grep and only falls through to vector search when the query actually looks semantic. Worth shipping?”
GrepFirst McFallthrough
Only 50% claw their way to "not bad." Faint praise is still praise.
“Finally, someone who remembers that grep is O(n) and your RAM isn't free.”
An MCP-native retrieval router that classifies incoming queries as lexical vs. semantic and dispatches to ripgrep or a vector store accordingly, with zero config defaults.
The MCP tooling layer is genuinely underbuilt right now and retrieval routing is a real unsolved DX problem. grep-first is the correct default that almost nobody implements — everyone cargo-cults vector search. This is small enough to ship fast and specific enough to find an audience in the Claude/Cursor power-user community immediately.
Viability Analysis
Pros & Cons
What's going for it
What's against it
Who You're Up Against
Open Source Alternatives
When Will Big AI Kill This?
Most Likely Killer
Anthropic
Timeline: 9-18 months
How They'll Do It
They add a retrieval_strategy hint to the MCP spec or ship a reference retrieval server with hybrid routing baked in, making your router redundant by default
Your Survival Strategy
Own the classification logic as a reusable library that works regardless of transport — make GrepFirst the algorithm, not just the MCP server
Confidence
If You're Crazy Enough to Build It
Solo Dev Time
1 focused weekend for v0.1, 3 weeks to handle edge cases you'll regret ignoring
Team Size
One developer who has strong opinions about BM25 and isn't afraid to read ripgrep source code
Estimated Cost
$0 in infra if local, ~$20/month if you add a hosted demo with embeddings API calls
Tech Stack
How this was generated
Production-readiness odds
Real readiness gaps. Build a thin first, harden second; budget runway for both.
ANCHORED TO OUR OWN READINESS RUBRIC — NO EXTERNAL STAT CITED
🛡 Safety considerations
What these mean →Heuristic, not exhaustive. Surfaces the 3 biggest categories an operator should think about for this idea. Hover any chip for the mitigation pointer.
⚖ Governance checklist
7 controls applyThings to have in place before you ship. Pairs with the OWASP-style risk chips above — that catalog answers “what could go wrong?”, this one answers “what should you have ready?”
Audit trail of every tool call
criticalPersist a structured per-call log of inputs, outputs, and decisions for at least the legal retention window. Without this, post-incident review is impossible.
Role-based access control on the agent surface
criticalDifferent users, different scopes. The agent should never default to "admin can do everything." Pair with per-task capability scoping.
Tenant / workspace isolation
criticalA multi-tenant agent must never leak data across tenants in either direction (inputs OR cached intermediate state).
Secrets management
highTokens and API keys live in a vault, not in env vars on a CI runner. Rotate on a documented schedule, not "when something happens."
Eval coverage on every release
highA frozen eval suite that runs on every model / prompt change. "It worked when I demoed it" is not a release gate.
Per-user / per-tenant rate limits
mediumAgent loops are pathologically expensive when wrong. Cap tokens-per-session, tool-calls-per-session, and dollars-per-day before launch.
Pin model versions; track the changelog
mediumA silent provider-side model upgrade can shift behavior overnight. Pin to a versioned model ID; subscribe to the provider changelog.
OUR INTERNAL TWELVE-CONTROL SYNTHESIS — STANDARD SOC 2 / ISO 27001 / GDPR FAMILIES APPLIED TO LLM AGENTS
Agent-Readiness Score
Worth building, but plan for the long-tail. GrepFirst McFallthrough needs runway, not just speed.
- Memory ↗21/25
Some cross-session state — start with Redis, graduate to a vector store.
- Tools ↗9/25
Crowded market: at least 8 integrations to compete.
- Policy ↗11/25
Mid-size policy surface — define refusal categories before launch.
- Evals ↗17/25
Eval scaffolding doable — write 50 paired examples and grade with an LLM-as-judge.
DETERMINISTIC SCORE — DERIVED FROM EXISTING ANALYSIS, NO SECOND LLM CALL
⚡ Scope it live
Want this agent scoped live? Book 20 min — free.
Walk through the verdict (actually not bad), the killer in your kill prediction, and one realistic scope. No signup, no slides — just 20 minutes to map what to build, what to skip, and what already exists.
Book 20 min — freeOpens Cal.com in a new tab · no signup on this site, ever.
🛠 Build this with Claude Code
Skip the boilerplate. Start from a working spec.
We've packaged this idea into a CLAUDE.md + scaffold.sh starter — the problem statement, agent-readiness sub-scores, suggested tools, and smoke evals, all deterministic and ready to drop into a fresh repo. Open it in Claude Code, or copy the markdown into any IDE.
Don't have Claude Code yet? View the bootstrap preview · grab the JSON bundle · or embed the readiness badge.
🛠 Steal this idea
Going to build GrepFirst McFallthrough? Claim it.
Post a public 2-paragraph plan. Add the repo URL when you ship. No rights granted; no permission required — credit goes to whoever ships first. See all claims at /steal-this-idea.
Want to actually build this?
Work with me to ship it.
Survived the verdict? Good. Let's build the damn thing.
Got another problem that needs an agent?
Roast My Problemwhycantwehaveanagentforthis.com