Llmkit

io.github.smigolsmigolPublished by GitHub account smigolsmigolv0.4.10Updated Oct 25, 2026

AI cost tracking: 11 tools for spend, budgets, and Claude Code + Cursor + Cline costs

VerifiedSTDIODesktop onlyFinanceData & AnalyticsAI & ML

Overview

AI-generated overview

A local MCP server that lets an assistant inspect AI coding-session costs and, with an LLMKit key, query spend, budgets, keys and service health.

What you can do
Inspect local coding sessions: read supported Claude Code sessions and Cline task data to see what agents cost, without an LLMKit key. Query gateway spend and budgets: check spend, budget state and sessions through the LLMKit gateway when a key is configured. Check keys and service health: look up API keys and gateway service status. Estimate costs from a bundled pricing catalog snapshot rather than live provider quotes.
When to use it
Useful when you want an assistant to report what Claude Code, Cursor or Cline sessions cost, or to check spend and budget status against an existing LLMKit gateway account. Local inspection works without an account; gateway queries need an existing key.
Requirements
Runs locally over stdio, typically started with npx from the npm package, so Node.js is needed. The LLMKIT_API_KEY environment variable is optional and only enables the gateway tools; local tools work without it. LLMKIT_PROXY_URL optionally overrides the default hosted proxy. Account creation and key management are currently unavailable, so an existing key is required for gateway features.
Before you install
The gateway tools send queries to the hosted LLMKit proxy by default, so spend, budget, key and session data leave the machine unless LLMKIT_PROXY_URL points elsewhere. LLMKIT_API_KEY is a secret and should be supplied through the environment, not committed. Local tools read Claude Code session and Cline task data on disk. Pricing is a bundled estimate, not a provider invoice.

Installation

In SourceWeft

  1. Open Llmkit in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

[LLMKit]

Measure what your AI agents cost. Stop requests before they exceed a budget.

[CI] [PyPI] [npm] [OpenSSF Scorecard] [OpenSSF Best Practices] [MIT license]

Website | Docs | Pricing API | Architecture | Security | Assurance case

LLMKit is an open-source AI gateway and SDK suite for cost attribution, budget admission, and request evidence. The gateway reserves estimated spend before provider dispatch. It rejects requests that cannot fit the active budget, then settles admitted reservations to actual usage when the response completes.

The repository also ships local tracking surfaces that do not require an LLMKit account or proxy.

Choose a surface

SurfaceUse it whenPackage
Python transportYou want local cost estimates around existing SDK callsllmkit-sdk
CLI wrapperYour OpenAI or Anthropic client honors its standard base-URL environment variable@f3d1/llmkit-cli
TypeScript SDKYou have an existing key and want sessions, streaming, and gateway access from TypeScript@f3d1/llmkit-sdk
MCP serverYou want spend, budget, and local coding-session tools inside an MCP client@f3d1/llmkit-mcp-server
AI SDK providerYou use Vercel AI SDK 6@f3d1/llmkit-ai-sdk-provider
Gateway and dashboardYou need shared budgets, provider routing, receipts, and analyticspackages/proxy, packages/dashboard

Quick start

Local Python tracking

bash
pip install llmkit-sdk
python
from llmkit import trackedfrom openai import OpenAI
costs = []client = OpenAI(http_client=tracked(on_cost=costs.append))
client.chat.completions.create(    model="gpt-4.1",    messages=[{"role": "user", "content": "Summarize this incident."}],)
print(f"${sum(item.total_cost or 0 for item in costs):.6f}")

The transport reads provider usage metadata and estimates cost from the bundled pricing catalog. It does not send tracking data to LLMKit.

Zero-code CLI tracking

bash
npx @f3d1/llmkit-cli -- python my_agent.py

Use -v for per-request output or --json for machine-readable results.

Gateway mode (existing key)

Gateway examples require an existing LLMKit API key. Account creation and key management are temporarily unavailable while the authenticated service is restored. If you do not already have a key, use one of the local tracking paths above.

python
from openai import OpenAI
client = OpenAI(    base_url="https://api.llmkit.sh/v1",    api_key="llmk_your_key_here",)
response = client.chat.completions.create(    model="gpt-4.1",    messages=[{"role": "user", "content": "Draft a release note."}],)

The budget path

[LLMKit authenticates each request, reserves its estimated cost, rejects requests over budget before provider dispatch, and settles admitted requests to actual usage.]

The control path is built around three boundaries:

  • Atomic admission: a Durable Object owns reservation state for each budget scope. Concurrent requests cannot spend the same remaining balance.
  • Dispatch-aware idempotency: deterministic failures before dispatch release the key. After provider dispatch may have occurred, failures remain terminal to avoid duplicate spend.
  • Bounded responses: non-streaming bodies and individual SSE frames have explicit byte limits. LLMKit cancels upstream reads when a limit is exceeded.

Request receipts bind the admission decision, provider attempt, settlement, and analytics handoff with stable identifiers. Database writes use an outbox, so an analytics outage does not silently erase budget evidence.

MCP server

json
{  "mcpServers": {    "llmkit": {      "command": "npx",      "args": ["-y", "@f3d1/llmkit-mcp-server"]    }  }}

Five local tools inspect supported Claude Code sessions and Cline task data without an LLMKit key. Six gateway tools query spend, budgets, keys, sessions, and service health when LLMKIT_API_KEY contains an existing key. Together they expose 11 tools.

Pricing data

The pinned catalog is a bundled reference snapshot, not a live quote. One source file, packages/shared/pricing.json, records the snapshot date and generates the TypeScript, Python, and MCP tables. CI rejects drift between the source and generated files. The public site renders only populated provider tables and displays the source date.

The public comparison endpoint requires no account:

text
https://api.llmkit.sh/v1/pricing/compare?mode=text-token&models=anthropic%2Fclaude-sonnet-4-6%2Copenai%2Fgpt-4o&input=1000&output=1000&cacheRead=0&cacheWrite=0

The endpoint prices only the exact model keys supplied by the caller. It does not search for or recommend the cheapest model. Pricing is an estimate, not a provider invoice. Provider billing rules, model modality, and catalog freshness remain part of the error boundary.

Evidence and current boundary

ClaimEvidence in this repositoryBoundary
Concurrent budget admission is serializedWorker fixtures exercise competing reservations, retries, settlement, and recoveryDeterministic local Worker and database proof
Retry behavior avoids duplicate dispatchIdempotency tests cover payload mismatch, pre-dispatch release, and post-dispatch indeterminate stateProvider behavior is simulated in CI
Large provider responses are boundedSuccess, error, and unterminated SSE fixtures verify rejection and stream cancellationBound is per buffered response or SSE frame
Pricing artifacts are reproducibleOne generator and CI --check path cover all published language tablesCatalog values still require source updates
Hosted recovery can be evaluated safelyGuarded staging deploy and proof runners bind an isolated Worker, database, revision, and cleanup journalA completed hosted concurrency and outage-recovery receipt is not claimed here

See STAGING_PROOF.md for the isolated hosted proof contract. It deliberately refuses production targets and dirty worktrees.

Project policy and design

DocumentWhat it owns
GovernanceDecision authority, roles, disputes, and the current continuity gap
RoadmapIntended and excluded work through August 2027
ArchitectureComponents, request flows, identity, storage, deployment, and failure boundaries
SecuritySecurity requirements, excluded guarantees, reporting, and supported versions
Security assuranceThreat model, trust boundaries, executable evidence, residual risks, and runtime HOLDs
AccessibilityPublic-site controls, verification method, known gaps, and language scope
ContributingSetup, quality gates, review expectations, and DCO sign-off

Development

bash
git clone https://github.com/smigolsmigol/llmkitcd llmkitcorepack [email protected] install --frozen-lockfilecorepack [email protected] buildcorepack [email protected] quality:pr

Run the Worker locally with development-only bindings:

bash
corepack [email protected] --filter @f3d1/llmkit-proxy dev

Generic deploy commands are intentionally omitted. Staging and production use separate guarded scripts with explicit target confirmation.

Security

Provider credentials are encrypted with AES-256-GCM using a random IV and owner/provider-bound additional authenticated data. LLMKit API keys are hashed before storage. CI includes secret scanning, static analysis, dependency review, CodeQL, and package provenance checks.

Read the security policy and architecture and the machine-readable Security Insights snapshot. Please report vulnerabilities through GitHub private vulnerability reporting or email [email protected].

License

MIT

Source: README.md at commit fc92e59

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.4.10LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts