# Skim > Runtime token proxy + intelligence dashboard for LLM tools. Intercepts API calls, strips waste, tracks costs — for individual developers and Fortune 500 teams. - **Type:** MCP server - **Install:** `agentstack add mcp-bb1nfosec-skim` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [bb1nfosec](https://agentstack.voostack.com/s/bb1nfosec) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [bb1nfosec](https://github.com/bb1nfosec) - **Source:** https://github.com/bb1nfosec/skim - **Website:** https://github.com/bb1nfosec/skim ## Install ```sh agentstack add mcp-bb1nfosec-skim ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # `skim` ### Stop paying for tokens you never meant to send. The runtime layer that sits between your AI tools and the LLM API — **stripping waste, injecting caching, and showing you exactly where every token goes.** [](https://pypi.org/project/skim-llm/) [](https://pypi.org/project/skim-llm/) [](https://www.python.org/) [](LICENSE) [](pyproject.toml) [**⚡ Quickstart**](#-quickstart)  ·  [**🔍 How it works**](#-how-it-works)  ·  [**📊 Dashboard**](#-dashboard)  ·  [**🏢 Enterprise**](#-enterprise)  ·  [**⌨️ CLI**](#️-cli-reference)  ·  [**📚 Docs**](docs/)  ·  [**▶️ Live Demo**](https://demo-mu-ten-60.vercel.app) > [!NOTE] > **One env var. Zero code changes.** Claude Code reads a `package-lock.json` — 122k tokens, $0.37 — just to answer a question about a 200-line file. History compounds. Your context window fills silently and quality degrades while you fly blind. skim fixes this in the API call path, in real time. ```mermaid flowchart LR A["🤖 Claude CodeCursor · your app"] -->|ANTHROPIC_BASE_URL| B1 subgraph SKIM ["⚡ skim proxy"] direction TB B1["✂️ strip lock files& build artifacts"] B2["◈ inject prompt caching50–90% cheaper"] B3["🛡️ enforce budgetshard 429 block"] B4["📊 live dashboard+ local SQLite"] B1 --> B2 --> B3 --> B4 end B4 --> C["☁️ AnthropicOpenAI · Gemini"] style A fill:#161920,stroke:#6c63ff,color:#e4e6f0 style SKIM fill:#0d0f14,stroke:#6c63ff,color:#6c63ff style C fill:#161920,stroke:#00d4aa,color:#e4e6f0 style B1 fill:#161920,stroke:#252a3a,color:#e4e6f0 style B2 fill:#161920,stroke:#252a3a,color:#e4e6f0 style B3 fill:#161920,stroke:#252a3a,color:#e4e6f0 style B4 fill:#161920,stroke:#252a3a,color:#e4e6f0 ``` ## ⚡ Quickstart **1. Install** ```bash pip install skim-llm ``` **2. Start the proxy** ```bash skim proxy ``` Browser opens automatically to your live dashboard. **3. Point your tool at it** ```bash export ANTHROPIC_API_KEY=sk-ant-... # required for Claude Code export ANTHROPIC_BASE_URL=http://localhost:7474 ``` **That's it.** Every call now flows through skim. ``` ┌────────────────────────────────────┐ │ skim v0.5.0 — runtime token proxy │ ├────────────────────────────────────┤ │ listening localhost:7474 │ │ dashboard localhost:7474/dashboard│ │ filtering ✓ on │ │ caching ✓ on │ ├────────────────────────────────────┤ │ ⠋ LIVE waiting for calls... │ └────────────────────────────────────┘ ``` > [!TIP] > **skim auto-detects your plan** — `x-api-key` for API users, `Authorization: Bearer` for OAuth clients — and routes each accordingly, with full waste filtering and tracking either way. > [!WARNING] > **Claude Code on a Pro/Max subscription cannot use a local proxy.** Subscription traffic ignores `ANTHROPIC_BASE_URL` and routes straight to Anthropic — the proxy will sit on "waiting for calls". To intercept Claude Code, use **API-key auth** (`export ANTHROPIC_API_KEY=sk-ant-…` alongside `ANTHROPIC_BASE_URL`, in the same shell before launching `claude`). skim also works as-is with **Cursor, the SDK, and any OpenAI-compatible tool**. ## 🔍 How it works ### ✂️ **Waste filtering** Detects lock files, build artifacts & generated code inside `tool_result` blocks and strips them before they hit your context. `package-lock.json` → a 12-token note instead of 122k tokens. ### ◈ **Caching injection** Wraps your system prompt + large context with `cache_control` automatically. First call caches it. Every call after is **free**. CLAUDE.md loads at zero cost on calls 2+. ### 📊 **Live dashboard** Opens in your browser on start. No login, no setup. Persists to `~/.skim/events.db`. Real-time SSE updates — watch tokens & cost as they happen. Auto-detected waste signatures | File | Detected by | |------|-------------| | `package-lock.json` | `"lockfileVersion"` + `"resolved": "https://"` | | `yarn.lock` | `# yarn lockfile v1` + `resolved` | | `pnpm-lock.yaml` | `lockfileVersion:` + `resolution:` | | `Cargo.lock` | `@generated` + `[[package]]` | | `poetry.lock` | `@generated` + `[[package]]` | | `composer.lock` | `"content-hash":` + `"packages":` | Plus anything in your project's `.llmignore`. Stripped blocks are replaced with a one-line note showing what was removed and how to disable it. How plan detection works One method, `_auth_type()`, owns all routing logic: ```python _auth_type() → ("apikey", key) # API plan → filtering + caching + tracking → ("oauth", token) # Pro/Max plan → filtering + tracking (no cache injection) → ("", "") # no auth → 401 ``` Adding a new plan type (enterprise SSO, team tokens) is a single `elif`. Caching injection is skipped for Pro/OAuth because the Pro plan manages its own cache layer. ## 📊 Dashboard Five fully-built pages. Dark theme, live charts, real-time SSE updates — no refresh button needed. | 🟣 Overview | ⚡ Sessions | 📈 Usage | 🤖 Models | 💰 Savings | |:---:|:---:|:---:|:---:|:---:| | tokens, cost,savings, cache | full call log,searchable | hourly +daily charts | cost/1k,cache %, waste % | cumulativesavings & ROI | ```bash skim proxy # local dashboard, zero setup, opens in browser ``` The local dashboard works for everyone — solo devs, Pro users, anyone. Data never leaves your machine unless you explicitly connect a team server. ## 🏢 Enterprise > [!IMPORTANT] > Everything below is **open-source and self-hosted** — same pip package, no paywall, no telemetry. #### 🛡️ Budget enforcement Hard-block calls that exceed token/cost limits. Proxy returns `429` before forwarding. ```bash skim admin budget set --owner-type team \ --owner-id engineering --usd 500 --period monthly ``` #### 🔔 Webhook alerts Slack (& Teams) or any HTTP endpoint on budget events. ```bash skim admin webhooks add --channel slack \ --url https://hooks.slack.com/... ``` #### ✉️ User invites Self-registration via single-use links. No manual accounts. ```bash skim admin users invite --email new@corp.com \ --role user --team platform ``` #### 🔑 Scoped API keys `ingest` · `read` · `admin` — with expiry dates and revocation. #### 👥 RBAC `admin` · `team_admin` · `user` — enforced data isolation per role. #### 📋 Audit log Every sensitive action logged immutably. Queryable by action + date. ```bash skim admin audit --days 30 --action auth.login ``` #### 📤 Data export CSV event logs + JSON summaries for accounting & BI. ```bash skim admin export --days 30 --out report.csv ``` Team deployment in 3 commands ```bash # 1. Run the server (auto-creates admin, uses gunicorn if installed) pip install 'skim-llm[web]' SKIM_ADMIN_EMAIL=you@corp.com skim server --host 0.0.0.0 --port 7475 # 2. Each developer connects their proxy export SKIM_SERVER_URL=https://skim.corp.internal export SKIM_SERVER_TOKEN=sk-skim-... # generate in Settings # 3. Manage from anywhere skim admin users list ``` **Auth:** local password · LDAP/AD (`SKIM_LDAP_*`) · Google/GitHub/Azure/Okta (`SKIM_OIDC_*`) Full guide → [docs/enterprise.md](docs/enterprise.md) · [docs/deployment.md](docs/deployment.md) ## ⌨️ CLI Reference **🔬 Static analysis**  no API key ```bash skim scan # token cost per file skim analyze # detect waste patterns skim fix # auto-write .llmignore skim check # CI budget gate skim generate # .llmignore + CLAUDE.md skim secrets # leaked credential scan ``` **⚙️ Runtime & ops** ```bash skim proxy # the interceptor skim server # team dashboard + API skim admin # manage users/budgets/keys skim audit # local operation log skim hooks # git pre-commit gate skim baseline # token regression checks ``` Example — skim fix auto-cleanup ``` skim fix — ./my-project ────────────────────────────────────────────────────── Before : 166.8k tokens (83.4% ctx) $0.50/session Pattern Severity Tokens saved Rules ──────────────────────────────────────────────────── Lock files HIGH 160.3k +7 Test snapshots MEDIUM 4.1k +2 ✓ Written to .llmignore After : 6.5k tokens (3.2% ctx) $0.02/session Saved : 160.3k tokens (96.1% reduction) $0.48/session Now : 51 sessions / $1 ``` ## 🐍 Python API ```python from adapters import ClaudeAdapter claude = ClaudeAdapter( model="claude-sonnet-4-6", system_prompt="You are a terse coding assistant.", enable_caching=True, # prompt caching, automatic ) response = claude.chat("Refactor the auth module") claude.print_stats() # Session: 12,400 tokens | Cache hit rate: 87% | Cost: $0.0037 ``` Adapters: `ClaudeAdapter` · `OpenAIAdapter` · `GeminiAdapter` · `OllamaAdapter` ## 📦 Install ```bash pip install skim-llm # core — zero hard deps pip install 'skim-llm[tiktoken]' # accurate token counting pip install 'skim-llm[web]' # dashboard server pip install 'skim-llm[web,sso,ldap]' # enterprise auth pip install 'skim-llm[all]' # everything ``` ## 📚 Documentation | Guide | What it covers | |:------|:---------------| | [**Quickstart**](docs/quickstart.md) | Zero to running in 2 minutes | | [**Proxy**](docs/proxy.md) | Deep-dive — every feature, every flag | | [**Dashboard**](docs/dashboard.md) | Local & team dashboards | | [**Enterprise**](docs/enterprise.md) | Budgets, webhooks, invites, RBAC, audit | | [**Admin CLI**](docs/admin-cli.md) | `skim admin` complete reference | | [**REST API**](docs/api.md) | All 31 endpoints with schemas | | [**Configuration**](docs/configuration.md) | Every env var & `.skimrc` option | | [**Deployment**](docs/deployment.md) | Docker, systemd, nginx, scaling | | [**MCP Setup**](docs/mcp-setup.md) | Claude Desktop integration | ## 🔌 MCP Server ```json { "mcpServers": { "skim": { "command": "skim-mcp" } } } ``` Tools: `scan_tokens` · `analyze_context` · `check_budget` · `fix_context` · `generate_llmignore` --- **[GitHub](https://github.com/bb1nfosec/skim)** · **[PyPI](https://pypi.org/project/skim-llm/)** · **[Issues](https://github.com/bb1nfosec/skim/issues)** · **[Changelog](CHANGELOG.md)** · **[Live Demo](https://demo-mu-ten-60.vercel.app)** Built for developers who'd rather not pay for noise. · MIT License ⭐ Star the repo if skim saved you some tokens. ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [bb1nfosec](https://github.com/bb1nfosec) - **Source:** [bb1nfosec/skim](https://github.com/bb1nfosec/skim) - **License:** MIT - **Homepage:** https://github.com/bb1nfosec/skim Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-bb1nfosec-skim - Seller: https://agentstack.voostack.com/s/bb1nfosec - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.