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observer

Track what every AI coding agent costs and see the limit coming. Per-session, per-model cost for Claude Code, Codex, Cursor and 37 more tools from your provider's own token counts, plus limit gauges, a dangerous-command guard and dashboard terminals. Free, Apache-2.0, runs on your machine.

Install / Use

claude mcp add superbasedapp -- npx -y github:superbasedapp/observer

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

78/100

Supported Platforms

Claude Code
Claude Desktop
Cursor
GitHub Copilot
Gemini CLI
OpenAI Codex

Our assessment of observer

observer scores 78/100 on our quality scale, 802nd of 962 AI & Machine Learning skills we index.

Its MCP Server is 61 KB long, well organised into 59 sections with 16 code examples: long enough that it reads more like full documentation than a focused instruction file, which agents can find harder to follow.

It has 50 GitHub stars, a meaningful sign that others use it.

Substance
21/30
Structure
20/20
Description
15/15
Adoption
7/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 7 days ago, so observer is actively maintained.
  • Our last check on 2026-10-21 found the source still online.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

observer compared with similar skills

All 4 of these similar skills score higher than observer; compare them before choosing.

SkillScoreStarsUpdatedFormat
observer (this skill)by superbasedapp78507d agoMCP Server
claude-memby thedotmack100102.1ktodayCLAUDE.md
Agent-Reachby Panniantong100100.5k1d agoCLAUDE.md
Understand-Anythingby Egonex-AI10087.4ktodayCLAUDE.md
headroomby headroomlabs-ai10077.0ktodayCLAUDE.md

Frequently asked questions

How do I install observer?
Run claude mcp add superbasedapp -- npx -y github:superbasedapp/observer. The install tabs above show the steps for each supported agent.
Which AI agents does observer work with?
It is written for Claude Code, Claude Desktop, Cursor, GitHub Copilot, Gemini CLI and OpenAI Codex, as a MCP Server file. Other agents that read the same format can often use it too.
Is observer safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is observer still maintained?
The repository was last updated 7 days ago, so observer is actively maintained.

SuperBased

The exact tokens your AI provider billed you — cache splits, reasoning tokens, long-context surcharges — reconciled across 40 coding tools, entirely on your own machine. Nothing you build here ever leaves your machine unless you opt a node into it.

npm License: Apache 2.0 Platforms: Linux • macOS • Windows Go 1.22+ ⭐ Star this repo

If SuperBased catches something useful in your next bill, a star helps other people looking for the same thing find it.

<p align="center"> <img src="docs/assets/infographics/one-local-path.png" alt="One local path for AI coding activity" width="780"> </p>

Try it in one command

npx @superbased/observer

On a fresh machine — no ~/.observer/observer.db, no ~/.observer/config.toml — this scans every AI coding tool's own local session files into a throwaway temp database, prints one cost table grouped by tool and model, and deletes the database again before it exits. It's local-only: zero network calls, and nothing is written outside that temp directory (foreign-mount adapter mirrors — e.g. WSL reading a Windows-side tool store — are redirected there too; pricing is embedded in the binary, not fetched at runtime).

Already have SuperBased set up (or want the explicit form)? Run observer usage. Bare observer only runs the one-shot on a machine with no local SuperBased state at all — otherwise it prints the usual welcome screen (OBSERVER_ONESHOT=off to always get the welcome screen). This is the zero-config sibling of observer cost: usage rolls up whatever session files it finds into a throwaway DB; cost queries the DB you've actually been capturing into with observer scan / observer start — including any proxy-accurate turns. Full reference: docs/one-shot-usage-report.md.


Table of contents


What it is in 30 seconds

A single local Go binary built on three things a hosted usage console can't give you, in order of how much they matter:

  1. Proxy-accurate, cross-vendor cost attribution. An optional API reverse proxy reads the token counts your provider actually billed — net input, 5m/1h cache read/write splits, reasoning tokens, long-context repricing — the same math your invoice uses, not a JSONL-derived estimate. It's accurate enough that it caught its own bug: a Codex reasoning-token double-billing regression SuperBased found and back-corrected months of history for (migration 058, shipped v1.18.0) — the kind of self-audit a vendor console has no incentive to run against itself.
  2. Local-first, by construction. The watcher, proxy, dashboard, MCP server, and CLI make zero outbound calls on your behalf — no telemetry, no analytics, no remote reporting. Everything SuperBased captures is written to your own database and stays there. Full details: PRIVACY.md.
  3. One capture layer, every tool you actually use. 40 adapters — Claude Code, Codex, Cursor, Cline + Cline CLI, GitHub Copilot + Copilot CLI, Gemini CLI, OpenCode, Google Antigravity, Cowork, Hermes Agent, Kilo Code, Aider, Goose, Devin, Qoder, Crush, Grok, Kiro CLI, Kimi Code, Qwen Code, OpenClaw, Pi, Factory Droid, Open Interpreter, Command Code, and more — parsed into one normalized schema, queryable from a local dashboard, an MCP server (so the tools themselves can query it), and a CLI. (Five more *-web adapters cover ChatGPT/Claude.ai/Gemini/Copilot/Perplexity in the browser — those need the browser-capture extension, which today only installs unpacked; every tool listed above works out of the box.) Twenty-seven of those are also full CLI launchers you can run as real terminals — from the dashboard or your own shell, captured through the same pipeline — see Terminals below.

Raw token counting across tools is table stakes here — it's the substrate the accurate-cost layer above is built on, not the pitch.

One local binary. SuperBased captures, normalizes, and analyzes AI coding tool activity on your own machine: proxy-accurate cost, compression, cache tracking, and session handoff for every AI coding tool you run.

<p align="center"> <img src="docs/assets/screenshots/04-cost.png" alt="Cost tab — proxy-accurate per-model token buckets and dollar cost" width="900"> </p> <p align="center"> <img src="docs/assets/screenshots/11-session-detail.png" alt="Session detail — cost, token buckets, cost predictor and limit gauge" width="900"> </p> <p align="center"> <img src="docs/assets/infographics/intelligence-across-tools.png" alt="Shared local intelligence layer across tools" width="780"> </p>

It answers questions like:

  • Where did this week's $147 Claude bill come from — which projects, models, sessions, tool calls? And is that number the same one my provider's invoice would show?
  • Did I spend more on Opus or Sonnet? Are my Sonnet sessions hitting the long-context tier and getting repriced at 2×?
  • How much did I waste re-reading files that hadn't changed since the last read in the same session?
  • Could that trivial Opus session have been done by Sonnet for 1/5 the cost?
  • Across Claude Code, Cursor, and Codex working in the same repo, what files are touched by all three? Where are they stepping on each other?
  • What will my next message roughly cost — and how much of my 5-hour and weekly subscription limit is left before I hit it?
  • Where did my own OpenTelemetry-instrumented agent spend its tokens — with the proxy's exact per-span cost where it routed through the proxy?

Install

Pick whichever package manager fits your environment — npm and PyPI ship the same prebuilt binary from the same v* tag, version numbers kept in lock-step.

Via VS Code (Marketplace or Open VSX)

code --install-extension superbased.superbased-observer

The VS Code extension bundles the observer binary, lifts the dashboard / sidebar / status bar / file decorations into the editor, and contributes a terminal profile that pre-exports the proxy env vars so AI CLIs launched from it route through observer automatically. Cursor, VSCodium, and Windsurf install the same VSIX via Open VSX.

After install, VS Code's Get Started page surfaces an in-editor walkthrough; the long-form user guide lives at docs/vscode-extension-user-guide.md and the command + settings reference is at docs/vscode-extension.md.

Via npm (recommended for Node users)

npm install -g @superbased/observer
observer --version

Via pip / uv / pipx (recommended for Python users)

pip install superbased-observer            # plain pip
uv tool install superbased-observer        # uv (isolated env, fastest)
pipx install superbased-observer           # pipx (isolated env)
observer --version

Wheels ship for manylinux2014_{x86_64,aarch64}, macosx_*_{x86_64,arm64}, and win_amd64. uv tool and pipx keep the install isolated from your project's Python env — generally what you want for a CLI tool.

Via go install (latest main, builds locally)

go install github.com/marmutapp/superbased-observer/cmd/observer@latest
observer --version

Via direct download (pre-built per-platform archive)

Each tagged release attaches per-platform archives to the Releases page, verifiable against the published SHA256SUMS:

| Asset | Platform | Contents | |---|---|---| | observer-vX.Y.Z-linux-x64.tar.gz | Linux x86_64 | observer + antigravity-bridge.exe (for WSL2) | | observer-vX.Y.Z-linux-arm64.tar.gz | Linux arm64 | observer + antigravity-bridge.exe (for WSL2) | | observer-vX.Y.Z-darwin-x64.tar.gz | macOS Intel | observer | | observer-vX.Y.Z-darwin-arm64.tar.gz | macOS Apple Silicon | observer | | observer-vX.Y.Z-win32-x64.zip | Windows x86_64 | observer.exe | | SHA256SUMS | — | sha256 of all five archives |

# Linux x64 example — substitute your platform + version.
VERSION=v1.6.21
PLAT=linux-x64
curl -L -O https://github.com/superbasedapp/observer/releases/download/$VERSION/observer-$VERSION-$PLAT.tar.gz
curl -L -O https://github.com/superbasedapp/observer/releases/download/$VERSION/SHA256SUMS
shasum -a 256 -c SHA256SUMS --ignore-missing
tar -xzf observer-$VERSION-$PLAT.tar.gz
./observer --version

The binary is pure Go — no CGO, no external runtime dependencies. SQLite storage is pure-Go via modernc.org/sqlite. Single static binary; scp it anywhere it runs. Same artifacts ship to npm and to the Releases page (build-once-ship-everywhere CI), so the npm and direct-download paths produce byte-identical binaries.


First-run walkthrough

# 1. Start everything: proxy + watcher + dashboard in one foreground
#    process (ctrl-c to stop). Hooks auto-register for every detected
#    AI tool, and the dashboard opens in your browser
#    (http://localhost:8081; suppress with --no-open).
observer start

# 2. (another shell) Backfill from existing session logs so the
#    dashboard has history immediately rather than starting empty.
observer scan

From here the dashboard drives. On an empty database the Overview tab leads with a three-step onboarding checklist — and a demo mode offer if you'd rather look around first: one click seeds a temporary synthetic dataset so every chart renders with realistic data (your real observer.db is never read or written; a persistent banner marks demo state and one click clears it). The two checklist steps that matter:

  1. Route your AI tool through the proxy — accurate token counts and conversation compression both need it. On the Compression tab's Proxy banner, click your tool's status pill, then Route through the observer proxy…: the button previews the exact file change (Claude Code: an env.ANTHROPIC_BASE_URL entry in ~/.claude/settings.json; Codex: an observer model provider in ~/.codex/config.toml) and writes only on confirm. Durable — every later session routes automatically. The same section of the Settings → Connected tools panel offers a per-tool setup wizard (hooks / MCP / routing, one consent click per write) and a Launch button. Prefer the terminal? The same routing

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars50
CategoryAI
Updated7d ago
Forks7

Languages

Go

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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