A MCP server that dynamically routes tool selection for AI agents at runtime
AI agents loaded with 50 or more tools suffer severe accuracy degradation because the model must process every tool schema upfront, overwhelming the context window and confusing selection. There is no production runtime layer that intelligently surfaces only the tools relevant to the current task turn, measures selection accuracy, and hot-swaps the active toolset without restarting the agent. This MCP server sits between the agent and its tool registry, scoring relevance per-turn and injecting only the top-N tool schemas, keeping accuracy high as the registry grows.
Demand Breakdown
Social Proof 3 sources
Gap Assessment
4 tools exist (Anthropic Claude lazy tool loading (built-in), Bifrost MCP Gateway, Peta MCP Gateway, HumanLayer 12-factor-agents) but gaps remain: Client-side only, Claude-specific, no cross-model support, no relevance scoring per turn, no tool accuracy telemetry, no registry management across MCP servers.; No per-turn dynamic tool subset selection. Surfaces all registered tools to the model. No accuracy measurement or feedback loop..
Features7 agent-ready prompts
Competitive LandscapeFREE
| Product | Does | Missing |
|---|---|---|
| Anthropic Claude lazy tool loading (built-in) | Claude Code v2.1.7 ships opt-in lazy loading that defers tool schema injection until a tool is actually called, reducing startup context from ~75k tokens to ~8k tokens for large toolsets. | Client-side only, Claude-specific, no cross-model support, no relevance scoring per turn, no tool accuracy telemetry, no registry management across MCP servers. |
| Bifrost MCP Gateway | High-throughput MCP gateway written in Go. Handles auth, routing requests to multiple MCP servers, and aggregates tool lists. Latency overhead ~11µs. | No per-turn dynamic tool subset selection. Surfaces all registered tools to the model. No accuracy measurement or feedback loop. |
| Peta MCP Gateway | MCP gateway founded mid-2025 for production-ready tool access with monitoring and compliance. Aggregates tools from multiple MCP servers. | No semantic relevance scoring on tool subsets per agent turn. Presents full tool catalog to the model context. No accuracy drop detection. |
| HumanLayer 12-factor-agents | Open-source guide documenting patterns for reliable agents, including tool discipline and subset-per-phase design. 23k GitHub stars, referenced widely. | A documentation guide, not a runtime. No enforcement, no routing server, no accuracy measurement, no registry. Developers must implement the patterns manually per project. |
Leads29BUILDER
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