👁 See what your MCP servers cost you in tokens — and cut it. Records every MCP tool call, itemises the per-session tax each server charges. 100% local.
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
claude mcp add mcpwatch -- npx -y @sreelal727/mcpwatch{
"mcpServers": {
"mcpwatch": {
"command": "npx",
"args": ["-y", "@sreelal727/mcpwatch"]
}
}
}Resumen de MCP Servers
<div align="center">
# 👁 mcpwatch
**Every MCP server you've installed is charging you tokens on every single session.
See the bill — then cut it.**
mcpwatch records the real traffic between your coding agent (Claude Code, Codex, Cursor,
Claude Desktop) and your MCP servers, then itemises what that setup actually costs you in
context — and tells you exactly what to delete.
*One command. All local. Zero config. No account, ever.*
[](https://www.npmjs.com/package/@sreelal727/mcpwatch)
[](https://github.com/Sreelal727/mcpwatch/actions/workflows/ci.yml)
[](LICENSE)
[](package.json)
[](CONTRIBUTING.md)
<!-- demo.gif goes here before launch: record with scripts/seed-demo.ts --keep-running + mcpwatch ui -->
</div>
---
Here's what nobody tells you when you install an MCP server: **its tool definitions get
injected into your agent's context at the start of every single session, whether you use
that server or not.** A big vendor integration with 50 tools can cost you 15,000+ tokens
before you type a word. You pay it again on the next session, and the next.
On top of that you're paying for tool responses that return 200 kB when you needed one
row, calls that fail and get retried, and agents re-fetching things they already had.
None of it shows up anywhere. mcpwatch records the actual bytes on the wire and turns
them into an itemised bill.
## See your number in ten seconds
No setup, no restart, no waiting. This starts each MCP server you already have
configured, asks it for its tool list the way your client does, measures it, and shuts
it down:
```
npx @sreelal727/mcpwatch audit
```
```
Every new session pays ~9,262 tokens ($0.05) to load these tool definitions,
before you type a word:
github 8,825 tokens 52 tools 95% Cursor
filesystem 437 tokens 6 tools 5% Cursor
9,262 tokens every session
At 10 sessions a day that is ~2,778,600 tokens a month ($13.89 at $5/M) spent
before any work happens.
"github" alone is 95% of that. If you do not use it in every project, moving it to
the projects that need it is the single biggest win available to you.
```
That's the fixed cost, and it's knowable without recording anything.
## Then find out what you actually use
Which of those tools you *call* does need real traffic. Instrument once, work normally
for a day, and ask:
```
npx @sreelal727/mcpwatch init # then restart your client
npx @sreelal727/mcpwatch cost # a day later
```
```
Your MCP setup costs ~12,486 tokens per session before you type a word ($0.06 at $5/M tokens).
PER-SESSION TAX — tool definitions loaded into every new session:
github 10,762 tokens 46 tools, none used ← never called
filesystem 780 tokens 8 tools, 2 used
postgres 944 tokens 9 tools, 1 used
12,486 tokens, every session
AT YOUR ACTUAL PACE — 34.9 server startups/day over 11.3 days:
~4,362,755 tokens/month ($21.81) on tool definitions alone, before any work happens
~4,939,089 tokens/month ($24.70) all in
BIGGEST SAVINGS — ~1,510,287 tokens ($7.55) of the above bought you nothing:
1. 1,420,584 tokens (10,762 of them every session) — github: 46 tools loaded into
every session, never called
→ Remove "github" from your MCP config (or load it only in projects that need it).
2. 85,523 tokens — filesystem: 132 repeat calls with identical arguments in the same session
→ The agent re-fetched the same thing — usually a sign it lost the earlier result.
3. 4,180 tokens — postgres: 33 failed calls
→ Fix or remove postgres's failing calls — each one costs context and a retry too.
```
Look at those first two numbers together: **$21.81 of that $24.70 monthly bill is tool
definitions** — the cost of merely having servers configured, before your agent does a
single useful thing. And the largest one has never been called.
That's the point of the whole tool. Not "here is a dashboard, go find something," but
*delete this one line from your config and stop paying 10,762 tokens every session for a
server you have never once used.*
The projection uses **your** observed startup rate from **your** recording — it isn't a
guess, and it doesn't appear at all until there's enough history to be honest about.
(Install once with `npm i -g @sreelal727/mcpwatch` and every command is just `mcpwatch …`.)
## Your agent can read the bill too
`init` also registers mcpwatch as an MCP server, so your agent gets these tools with no
extra setup:
| Tool | The question it answers |
|---|---|
| `token_costs` | "What is my MCP setup costing me, and what should I remove?" |
| `recent_failures` | "What just broke, with what arguments, and what did the server say?" |
| `server_health` | "Is that server crashing, slow, hanging, or corrupting the protocol?" |
| `find_calls` | "Has this tool ever worked? What arguments did I use last time?" |
| `get_call` | "Show me the exact request and response JSON for call #412." |
So you can just ask, in the client you already use:
> **You:** my context keeps filling up, what's eating it?
>
> **Agent:** *(calls `token_costs`)* Your `github` server loads 46 tool definitions —
> 10,762 tokens — into every session, and you haven't called it once in the last 30 days.
> That's about 1.4M tokens over the window. Your filesystem server also re-read identical
> files 132 times. Want me to take github out of your config?
The descriptions are written as trigger conditions, so the agent reaches for them on its
own — `recent_failures` after a failed tool call, `token_costs` when you mention context
or cost — instead of waiting to be told they exist.
## It also tells you what's broken
The same recording answers the reliability questions, in one command:
```
$ mcpwatch doctor
2 error(s) in 19 MCP calls across 3 server(s) in the last 24h.
! web-fetch 5 calls, no errors, avg 152ms last seen 32s ago
1 non-protocol stdout line (this server logs to stdout, which corrupts MCP)
✗ database 7 calls, 2 errors (29%), avg 227ms last seen 34s ago
high error rate
slowest: run_query at 1.3s
✓ filesystem 7 calls, no errors, avg 54ms last seen 36s ago
[#14] 2s ago database/does_not_exist tool_error (2ms)
error: MCP error -32602: Tool does_not_exist not found
session fd14d19f · full payloads: get_call(14)
```
`mcpwatch tail` streams calls live, one line each. Everything takes `--json`, so agents
with only shell access (Codex in a VS Code terminal, hooks, CI) can read it too. And
`mcpwatch ui` opens a local dashboard on `127.0.0.1` when you'd rather look yourself.
## What you get
- **A number in ten seconds** — `mcpwatch audit` prices your configured servers with no
instrumentation, no client restart, and no waiting for traffic.
- **An itemised token bill** — `mcpwatch cost` prices every server's per-session tax,
projects it forward from your own usage, and ranks what to remove: unused servers,
bloated tool lists, oversized responses, repeated calls, failed calls.
- **Agent-readable recording** — `token_costs`, `recent_failures`, `server_health`,
`find_calls`, `get_call` as MCP tools, plus `--json` on everything for agents that
only have a shell. Your agent stops guessing about its own tool calls.
- **Live dashboard** — sessions stream in as your agent works: call timeline, status
dots, latency bars, full request/response JSON inspection, filtering, dark/light.
- **Every call recorded** — paired request/response with duration and status
(`ok` / `rpc_error` / `tool_error`), including in-band tool failures that clients
often swallow silently.
- **Misbehaving-server detection** — servers that write logs to stdout corrupt the MCP
protocol; mcpwatch records those lines and flags them instead of breaking.
- **Secret redaction, on by default** — API keys, bearer tokens, JWTs, and
password-shaped JSON fields are scrubbed from the *stored copy* (never the live
stream). `--no-redact` to disable, `MCPWATCH_REDACT_EXTRA` to add patterns.
- **Session export** — `mcpwatch export <id>` produces one self-contained HTML file:
a shareable, scriptless bug report of exactly what happened.
- **HTTP servers too** — `mcpwatch http <url>` is a recording reverse proxy for
Streamable HTTP servers (SSE responses included).
- **Your data, your disk** — `mcpwatch gc` for retention; delete `~/.mcpwatch` and
it's gone. No SaaS, no accounts, no telemetry, ever.
## How it works
```
your agent ──stdio──▶ mcpwatch run ──stdio──▶ your MCP server
▲ │
│ └── tee ──▶ SQLite (~/.mcpwatch)
│ │
└──── mcpwatch mcp ◀─────────────────────┤ the agent reads its own history
│
mcpwatch ui / doctor / tail ◀──────┘ you read it, when you want to
```
`mcpwatch init` rewrites each stdio server entry in your client's config to route
through `mcpwatch run`. The proxy pipes bytes through untouched and parses a *copy* of
the stream — capture is wired independently of passthrough, so even if recording fails,
your agent keeps working. **Passthrough is sacred** is design principle #1, enforced in
code and covered by end-to-end tests that drive a real MCP client through the proxy.
`init` also adds mcpwatch itself to your client as an MCP server, which closes the loop:
the recorder becomes a tool the agent can call. It is never wrapped by its own proxy —
otherwise every question the agent asked about the traffic would become more traffic.
## How it compares
| | mcpwatch | MCP InspectoLo que la gente pregunta sobre mcpwatch
¿Qué es Sreelal727/mcpwatch?
+
Sreelal727/mcpwatch es mcp servers para el ecosistema de Claude AI. 👁 See what your MCP servers cost you in tokens — and cut it. Records every MCP tool call, itemises the per-session tax each server charges. 100% local. Tiene 0 estrellas en GitHub y su última actualización registrada es del 2026-09-04.
¿Cómo se instala mcpwatch?
+
Puedes instalar mcpwatch clonando el repositorio (https://github.com/Sreelal727/mcpwatch) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar Sreelal727/mcpwatch?
+
Nuestro agente de seguridad ha analizado Sreelal727/mcpwatch y le ha asignado un Trust Score de 95/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene Sreelal727/mcpwatch?
+
Sreelal727/mcpwatch es mantenido por Sreelal727. La última actividad registrada en GitHub es del 2026-09-04, con 5 issues abiertos.
¿Hay alternativas a mcpwatch?
+
Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.
Despliega mcpwatch en tu cloud
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