AI · alternatives · 2026
24 alternatives to Calling tools w/ Python improves LLM perf. vs MCP (77.1% on BrowseComp)
If agent's tools are exposed as functions/objects in a Python REPL (as opposed to JSON schemas) they perform better, I linked the explainer article we wrote, but if you want to jump straight in check out the docs! https://docs.symbolica.ai/
Symbolica is a Python-based tool framework that improves AI agent performance by exposing tools as native Python functions and objects in a REPL environment rather than JSON schemas. Designed for developers building AI… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Agenta▲362Open-source prompt management & evals for AI teams
Nov 2025 · agenta.ai · its alternatives →
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Resolve dev tasks & bugs faster with Webvizio MCP
2025 · webvizio.com · its alternatives →
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I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com · its alternatives →
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Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make…
Jul 2026 · microsoft.github.io · its alternatives →
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Your AI agent is burning 6x more tokens than it needs to just to browse the web. We built OpenBrowser MCP to fix that. Most browser MCPs give the LLM dozens of tools: click, scroll, type, extract, navigate. Each call dumps the entire page accessibility tree into the context window. One Wikipedia page? 124K+ tokens. Every. Single. Call. OpenBrowser works differently. It exposes one tool. Your agent writes Python code, and OpenBrowser executes it in a persistent runtime with full browser access. The agent controls what comes back. No bloated page dumps. No wasted tokens. Just the data your…
Apr 2026 · openbrowser.me · its alternatives →
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Hey HN, we’re building an open specification that lets agents discover and invoke APIs with natural language, built on the OpenAPI standard. agents.json clearly defines the contract between LLMs and API as a standard that's open, observable, and replicable. Here’s a walkthrough of how it works: https://youtu.be/kby2Wdt2Dtk?si=59xGCDy48Zzwr7ND. There’s 2 parts to this: 1. An agents.json file describes how to link API calls together into outcome-based tools for LLMs. This file sits alongside an OpenAPI file. 2. The agents.json SDK loads agents.json files as tools for an LLM that…
2025 · github.com · its alternatives →
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Code Mode▲144I’ve been testing a simple idea inspired by Apple/Cloudflare/Anthropic: LLMs are far better at writing a small program than coordinating multiple tool calls. So instead of giving the model 10+ tools, I exposed one: a TypeScript sandbox with access to the same interfaces. The model writes a script → it runs once → done. What changed - +68% reduction in token use - No multi-step drift or retries - Local models (Llama 3.1 8B / Phi-3) became much more reliable Repo: https://github.com/universal-tool-calling-protocol/code-mode Curious whether others have seen…
Nov 2025 · github.com · its alternatives →
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I'm Dan, and I built a CLI that lets AI agents design in Figma. What it does: 100 commands to create shapes, text, frames, components, modify styles, export assets. JSX importing that's ~100x faster than any plugin API import. Works with any LLM coding assistant. Why I built it: The official Figma MCP server can only read files. I wanted AI to actually design — create buttons, build layouts, generate entire component systems. Existing solutions were either read-only or required verbose JSON schemas that burn through tokens. Demo (45 sec): https://youtu.be/9eSYVZRle7o Tech…
Jan 2026 · github.com · its alternatives →
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Gram Functions▲119Hi HN, Georges from the Gram team here. We're really excited to share a major update to Gram, our platform for curating tools for agents, in the form of Gram Functions. Gram initially started out by letting users upload OpenAPI documents and turning them into tools that can be curated into small MCP servers that power your agentic use cases. We've known for quite some time that many existing REST APIs are simply not suitable as LLM tools and we wanted to solve this problem by letting users simply write code and we would take care of deploying that code for them and hosting MCP servers. We…
Nov 2025 · speakeasy.com · its alternatives →
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I've been building computer-use tools for a while, and I quietly launched this about a month ago (122 Stars on GH). I figured it was worth sharing here. Over the last few months, a lot of computer-use agents have come out: Codex, Claude Code, CUA, and others. Most of them seem to work roughly like this: 1. Take a screenshot 2. Have the model predict pixel coordinates 3. Click x,y 4. Take another screenshot 5. Repeat That works, but it's slow, expensive in tokens, and fragile. If the UI shifts a few pixels, things break. And the model still doesn't know what any element actually is. But the…
May 2026 · github.com · its alternatives →
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I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.
2025 · aicode.danvoronov.com · its alternatives →
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An Excel AI agent that uses MCP tools to let LLMs read, edit, and automate Excel spreadsheets. - SylvianAI/sv-excel-agent
Dec 2025 · github.com · its alternatives →
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Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…
2025 · github.com · its alternatives →
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Hey HN – Gregor & Magnus here again. A few months ago, we launched Browser Use (https://news.ycombinator.com/item?id=43173378), which let LLMs perform tasks in the browser using natural language prompts. It was great for one-off tasks like booking flights or finding products—but we soon realized enterprises have somewhat different needs: They typically have one workflow with dynamic variables (e.g., filling out a form and downloading a PDF) that they want to reliably run a million times without breaking. Pure LLM agents were slow, expensive, and unpredictable for these…
2025 · github.com · its alternatives →
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Run GPT-OSS, Qwen, Llama, and DeepSeek through one OpenAI-compatible API with streaming and clear usage-based pricing.
May 2026 · adola.app · its alternatives →
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LLM agents often place raw JSON tool outputs directly in the prompt. After a few tool calls, earlier results get compacted or truncated and answers become incorrect or inconsistent. I built Sift, a drop-in MCP gateway that stores tool outputs as local artifacts (filesystem blobs indexed in SQLite) and returns an `artifact_id` plus compact schema hints when responses are large or paginated. Instead of reasoning over full JSON in the prompt, the model runs a small Python query: def run(data, schema, params): return max(data, key=lambda x: x["magnitude"])["place"] Query code runs in a…
Mar 2026 · github.com · its alternatives →
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Current AI-assisted CLI tools are often part of larger systems and work better on Linux. I built llm-term to address these. It's a Rust-based tool that compiles into a single binary file. You only need to download the binary, add it to your PATH, and configure your OpenAI key to get started. While llm-term offers an option for gpt-4o, it works great with gpt-4o-mini. So it's not costly. I appreciate any feedback or suggestions.
2024 · github.com · its alternatives →
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We’ve built an AI risk assessment tool designed specifically for GenAI/LLM applications. It's still early, but we’d love your feedback. Here’s what it does: 1. it performs comprehensive AI risk assessments by analyzing your codebase against different AI regulation/framework or even internal policies. It identifies potential issues and suggests fixes directly through one click PRs. 2. the first framework the platform supports is OWASP Top 10 for LLM Applications 2025, upcoming framework will be ISO 42001 as well as custom policy documents. 3. we're a small, early stage team, so the…
2025 · gettavo.com · its alternatives →
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Enables small-to-large self-hosted ai models to use local source code when running tool-calling agentic workloads. We actively data mine 20,900+ (2+ TB) popular github repos using large and small ai models to create reuseable: json, markdown and parquet files for local-first tool-calling models. - d
May 2026 · github.com · its alternatives →
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Hey HN, I’m a physicist turned quant. Some friends and I 'built' SymDerive because we wanted a symbolic math library that was "Agent-Native" by design, but still a practical tool for humans. It boils down to two main goals: 1. Agent Reliability: I’ve found that AI agents write much more reliable code when they stick to stateless, functional pipelines (Lisp-style). It keeps them from hallucinating state changes or getting lost in long procedural scripts. I wanted a library that enforces that "Input -> Transform -> Output" flow by default. 2. Easing the transition to Python: For many…
Feb 2026 · its alternatives →
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I have built many AI agents, and all frameworks felt so bloated, slow, and unpredictable. Therefore, I hacked together a minimal library that works with JSON/dict/kwargs definitions for each step, allowing you a simpler way to define reproducible agents. It supports concurrency for up to 1000 calls/min, giving you speed and predictability in your workflows. Install pip install flashlearn Input is a list of dictionaries Simply take user inputs, API responses, and calculations from other tools and feed them to FlashLearn. user_inputs = [{"query": "When was python launched?"}]…
2025 · github.com · its alternatives →
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Hey HN! We just released Marvin 2.0. Marvin is an AI toolkit for developers who want to use LLMs with traditional software. We still see significant challenges integrating LLMs because of how difficult it is to get them to reliably accept and return structured data. Marvin consists of independent, functional tools that address this problem in a variety of ways. Marvin has always been focused on using LLMs to work with native Python datatypes and Pydantic models. In 2.0 we've expanded this significantly with dedicated APIs for the most common use cases we've seen over the last year:…
2024 · factsmachine.ai · its alternatives →
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LangGraph orchestration scaffold (Python) + restricted tool runner (Rust) with batching and run traces. - christianmeurer/Lula
Apr 2026 · github.com · its alternatives →
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