A web app that brings distributed tracing, cost attribution, and version management to MCP server deployments
Teams running multi-agent systems over MCP have no visibility into which tool calls cost what, which server version caused a regression, or how a request flowed across a chain of MCP servers. General-purpose LLM observability tools like Langfuse and Helicone trace at the model call level but are blind to the MCP protocol layer, leaving the hard-won lessons of distributed RPC systems (trace propagation, per-service cost budgets, version diffs, rollback) completely absent. This app gives MCP operators a production-grade control plane: trace every tool invocation end-to-end, attribute latency and token cost per server and tool, manage server versions with diff and rollback, and set per-team cost budgets.
Demand Breakdown
Social Proof 1 sources
Gap Assessment
4 tools exist (Langfuse, Helicone, Arize Phoenix, LangSmith) but gaps remain: Traces stop at the LLM API boundary; no MCP-protocol-level span propagation, no per-MCP-server cost attribution, no MCP version diff or rollback; Proxy sits between app and LLM, not between agent and MCP server; no MCP tool-call tracing, no version management, no distributed trace correlation across multi-hop MCP chains.
Features7 agent-ready prompts
Competitive LandscapeFREE
| Product | Does | Missing |
|---|---|---|
| Langfuse | Open-source LLM observability: traces model calls, tracks prompt versions, basic cost analytics at the model-provider level | Traces stop at the LLM API boundary; no MCP-protocol-level span propagation, no per-MCP-server cost attribution, no MCP version diff or rollback |
| Helicone | Proxy-based LLM request logging; multi-provider cost visibility; quick drop-in for raw LLM calls | Proxy sits between app and LLM, not between agent and MCP server; no MCP tool-call tracing, no version management, no distributed trace correlation across multi-hop MCP chains |
| Arize Phoenix | ML-grade observability with OpenTelemetry tracing, eval primitives, drift detection; Arize raised $70M Series C Feb 2025 | OTel plugin adds tracing but no MCP-specific semantics (tool name, server version, tool cost budget); no MCP version registry, no per-team cost caps at the server level |
| LangSmith | LangChain-native tracing, annotation queues, dataset management; deepest framework integration for LangChain/LangGraph users | Locked to LangChain ecosystem; no native MCP server version management; cost attribution is at model-call level not MCP server level; no multi-framework MCP chain tracing |
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