MCPSpendCompare · Langfuse
MCPSpend vs. Langfuse
Langfuse is the dev-time observability platform for LLM apps — traces, prompt versioning, evaluations. Excellent if you build the app and can drop their SDK into your code. MCPSpend is for the runtime layer of the AI agent ecosystem: you don't own the agent (Cursor, Claude Desktop), you don't own the MCP server (Playwright, filesystem), but you still want to know what each tool call costs. That's what we do, via config-only wrapping.
| Dimension | MCPSpend | Langfuse |
|---|---|---|
| Primary unit tracked | MCP tool call | LLM trace + evaluation |
| Install path | One CLI command, no code change in MCP servers | Add Langfuse SDK calls inside every MCP server you maintain |
| Wraps closed-source MCP servers | Yes (Playwright, filesystem, GitHub, anything stdio or HTTP) | No — needs SDK access to the server code |
| Sees Cursor / Claude Desktop agents | Yes — config-only wrap | Only if those IDEs ship Langfuse instrumentation (they don't) |
| Prompt versioning & evals | Out of scope (we focus on cost & usage) | Built-in — strong at this |
| Cost attribution per MCP tool | First-class | Possible with custom metadata |
| Per-project budget alerts | $ budget at 50/80/100% via email + Slack | Cost tracking yes; alerting via custom integration |
| Free tier | 25,000 tool calls / month forever | Generous free tier on self-hosted; cloud has its own limits |
| Paid entry point | $29 / month (Pro) | Cloud from ~$29 / month |
| Open source core | Proxy + MCP server MIT | Server is MIT, self-hosting friendly |
Choose MCPSpend if…
- ✓ You use MCP servers you didn't write (Playwright, filesystem, github, etc.)
- ✓ Your agents live in Cursor / Claude Desktop / Windsurf
- ✓ You want zero-code install — config wrap only
- ✓ Cost / usage is the core question, not trace replays
Choose Langfuse if…
- ✓ You build your own AI app and own the code path end-to-end
- ✓ Prompt versioning, A/B tests, and offline evals matter
- ✓ You want full LLM trace visualisation
- ✓ Self-hosting on your infra is a hard requirement
Different layers, often used together.
Langfuse on your app, MCPSpend on the MCP servers your app — or your IDE — calls. Full agent observability without overlap.