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Unified AI Search Gateway
Build a developer-facing gateway that sits on top of self-hosted search engines and exposes one stable API plus MCP support for AI agents. It solves fragmented compatibility, lets users swap backends without rewriting integrations, and adds reliability controls such as fallback and caching.
Why this matters
You are building a private search layer for AI workflows, but each backend behaves differently. One tool works better for browser search, another is kept alive only because your local LLM stack expects its API shape. You end up running duplicate services, testing community plugins, and worrying that a new release will break your agent setup. What you actually want is a stable interface that can point to whichever self-hosted engine is healthiest today, without making you rewrite prompts, plugins, or retrieval code every time the ecosystem shifts.
- · Built for Developers and technical teams building local LLM, agent, and private-search workflows who currently juggle multiple self-hosted search backends..
- · Most likely monetization: SaaS subscription.
The Pain · Narrative
You are building a private search layer for AI workflows, but each backend behaves differently. One tool works better for browser search, another is kept alive only because your local LLM stack expects its API shape. You end up running duplicate services, testing community plugins, and worrying that a new release will break your agent setup. What you actually want is a stable interface that can point to whichever self-hosted engine is healthiest today, without making you rewrite prompts, plugins, or retrieval code every time the ecosystem shifts.
Score Breakdown
Market Signal
Go-to-Market
Indie developers and small AI product teams running local or privacy-focused LLM agents that need web search access without relying on public search APIs.
~50K active globally in the early adopter segment
Hacker News launch
$19/month
15 paying teams or individuals using the gateway for at least 1,000 searches each within 30 days
MVP Scope · 1–2 weeks
- Implement a unified REST endpoint that forwards requests to two supported backends
- Normalize response schema for web, image, and snippet results
- Add simple health checks and timeout-based fallback between backends
- Create Docker deployment and sample compose file
- Publish minimal docs plus one SDK example for Python
- Add MCP server support for agent frameworks
- Implement result caching with TTL controls
- Build admin dashboard for backend status and request logs
- Add compatibility presets for common self-hosted search deployments
- Launch landing page with waitlist and self-serve billing
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1Upstream projects may rapidly improve API and MCP support, shrinking the need for a paid abstraction layer.
- 2Privacy-focused users may reject a hosted gateway if they believe it weakens their control over search data.
- 3The addressable market may be enthusiastic but too small to support a standalone company beyond a niche developer tool.
Evidence Summary
How AI synthesized this insight — no verbatim quotes
Several commenters described running multiple search tools at once because no single option covered browser use, reliability, and AI integration needs. Extensions, API compatibility, and MCP support came up repeatedly, while some users kept an older engine only for LLM workflows. That combination suggests a real demand for a unifying layer that reduces integration churn.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Build
Strong demand signals detected. Real pain, real willingness to pay — start building an MVP.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
Unified AI Search Gateway
Sub-headline
Build a developer-facing gateway that sits on top of self-hosted search engines and exposes one stable API plus MCP support for AI agents. It solves fragmented compatibility, lets users swap backends without rewriting integrations, and adds reliability controls such as fallback and caching.
Who It's For
For Developers and technical teams building local LLM, agent, and private-search workflows who currently juggle multiple self-hosted search backends.
Feature List
✓ Single search API that normalizes SearXNG-like and newer backends ✓ Built-in MCP server for agent frameworks ✓ Automatic backend failover, timeout tuning, and result caching
Where to Validate
Share your landing page in r/r/selfhosted — that's exactly where these pain points were discovered.
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