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A local gateway that lets every AI coding client share one set of MCP server connections instead of configuring each tool separately, cutting how many tools your agent has to load.
Watch out · The '91% overhead cut' figure is the product's own claim; we haven't independently benchmarked it.
FreeNo sign-upWorks offline
What to know▼
How it works
A local-first, open-source gateway. You set up and authenticate each MCP server once, and every connected AI client — Claude, Cursor, VS Code, Codex — shares that same connection instead of you configuring it per tool.
What's different
Claims up to 91% less tool-token overhead by giving an agent a handful of meta-tools instead of loading hundreds of individual tool definitions; API keys stay in the OS keychain.
Pricing
Free, open source, no sign-up.
Best for
Developers running multiple AI coding clients against the same set of MCP servers who don't want to re-authenticate each one separately.
Watch out
The '91% overhead cut' figure is the product's own claim; we haven't independently benchmarked it.
We check every product on this page once a day and record whether it still answers.
Generates a 3D model from a single image entirely on-device using WebGPU, with no server uploads or accounts needed — an open-source tool for developers experimenting with local image-to-3D generation.
Works offlineData stays with youOpen source
What to know▼
How it works
Generates a 3D model from a single image entirely on-device using WebGPU compute in the browser, with no server uploads or accounts.
What's different
Open source and runs locally via WebGPU rather than requiring cloud GPU processing, also deployable on Vercel for instant testing.
Best for
Developers experimenting with local, private image-to-3D generation.
We check every product on this page once a day and record whether it still answers.
A debugger for AI agent runs that shows exactly what context each model call saw, for developers troubleshooting agents built with Claude Code, Codex, or Cursor.
Works offlineOpen source
What to know▼
How it works
Captures every step of an agent run, compares two runs, and can fork from any step to test changes
What's different
Local-first and open source, so traces never leave your machine
We check every product on this page once a day and record whether it still answers.
Gives voice-AI developers one account to meter spend across their whole vendor stack (LLM, speech-to-text, text-to-speech, telephony) with spend caps and kill-switches.
Open source
What to know▼
How it works
Server-side spend caps and per-agent kill-switches across multiple vendor APIs under one key
What's different
Open-source floe-guard component
Best for
Developers building voice AI products across several paid vendor APIs
We check every product on this page once a day and record whether it still answers.
An open-source Python agent runtime, installed with one pip command, with a local cache that skips repeat LLM calls — pitched as a lighter alternative to LangGraph for developers.
Open source
What to know▼
How it works
An open-source agent graph runtime with a BSP scheduler and a local semantic cache that skips redundant LLM calls when a similar routing request already happened, installed with a single pip command.
What's different
Positioned as a lighter, non-wrapper alternative to LangGraph, with a local cache to cut LLM call costs.
Pricing
Open source (Apache-2.0).
Best for
Developers building LLM agent pipelines who want to reduce redundant model calls.
We check every product on this page once a day and record whether it still answers.
A self-hostable AI chat platform that routes queries to the cheapest LLM and adds live market data, positioned as an alternative to ChatGPT or Claude you run yourself. For developers and cost-conscious teams.
FreeOpen sourceSelf-hosted
What to know▼
How it works
A self-hostable, open-source AI chat platform that runs on your own infrastructure, integrates live financial market data into chat, and routes each query to the best/cheapest LLM automatically across OpenAI, Anthropic, SiliconFlow and others.
What's different
Self-hosted with full data ownership and no vendor lock-in, plus intelligent model routing claimed to cut API costs by up to 60% versus using a single provider.
Pricing
Free forever to self-host, with Free / Pro / MAX tiers and per-model quotas.
Best for
Developers and cost-conscious teams who want a ChatGPT/Claude alternative running on their own infrastructure.
We check every product on this page once a day and record whether it still answers.
Open-source API that compresses prompts before OpenAI, Claude, Gemini or RAG calls, cutting token costs by about 65% while keeping the important content. For developers wiring it into their own LLM calls.
Open source
What to know▼
How it works
An open-source API that compresses prompts before they're sent to OpenAI, Claude, Gemini, RAG, chatbot, or agent calls, stripping tokens while preserving the evidence needed to answer correctly.
What's different
Claims to remove more than 65% of tokens on average while preserving over 98% of answer-critical content.
Best for
Developers wiring their own LLM calls who want to cut token costs without integrating a full new pipeline.
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A local, open-source binary that meters and caps AI agent spend on your own machine for developers who want budget control without sending usage data to a dashboard.
Open source
What to know▼
How it works
A local binary sits in the request path, meters every token spent by AI agents, and enforces spend caps before they're exceeded; also compares your flat-rate plan against real metered rates.
What's different
Open source (MIT); sync and team budgets are planned but not yet available.
Best for
Developers running AI agents who want local spend control without a hosted dashboard.
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Open-source control plane that routes coding tasks across AI agents like Claude Code, Cursor, and Codex with cost tracking.
Open source
What to know▼
How it works
An open-source control plane that routes coding tasks across AI coding agents (Claude Code, Cursor, Codex, Wrangler, etc.), runs multi-agent workflows, caches to reduce repeated token spend, falls back on billing/availability issues, and shows cost per task with files touched.
What's different
Gives one measurable layer above multiple separate agent tools instead of running each independently.
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Cross-platform hardware monitoring with real-time stats, history and benchmarking for Windows, Linux, macOS and Android, with all data processed locally and no telemetry upload.
Works offlineOpen source
What to know▼
How it works
Monitors CPU, GPU, memory, disk and network in real time, with historical analytics, process management, local benchmarking, and gaming session detection, across Windows, Linux, macOS (Apple Silicon), and Android.
What's different
All monitoring data is processed on-device with local SQLite storage; no telemetry or benchmark results are uploaded.
Best for
Users who want cross-platform hardware monitoring without sending data to the cloud.
