Directory
107,857 agents from 4 public sources
Showing 1–24, most evidence first; contradicted and not yet assessed last · names and descriptions as their source publishes them
- Agent Data Tools: AIio.github.Nutshell2000/agent-data-tools-ai · agent-data-tools.revmesh2074.workers.dev37 tools: LLM chat, summaries, translation, embeddings, speech, images. 25 free calls.Livechecked Evidence 2/4MCPWebsiteMCP Registry
- Chat completions (LLM)agent-data-tools.revmesh2074.workers.devChat completions (LLM). Send a prompt, get an answer from Meta's Llama 4 Scout (17B active, 16 experts), with an optional system prompt, up to 1,024 output tokens and adjustable temperature. Fast and cheap. Use for drafting, reasoning steps, Q&A and any quick LLM call without an AI provider account; other open models by name at /v1/chat/completions, harder reasoning at ai_chat_large.Livechecked Evidence 1/4x402x402 Bazaar5 payers
- Image generation, generate imageagent-data-tools.revmesh2074.workers.devOpenAI-compatible image generation, pay per image: a prompt in, one 1024x1024 FLUX.1 schnell JPEG out as b64_json. No account or API key; failed calls are not charged.Livechecked Evidence 1/4x402x402 Bazaar4 payers
- OpenAI compatible embeddingsagent-data-tools.revmesh2074.workers.devOpenAI compatible embeddings. A 1,024-dimension embedding vector for up to 4,000 characters of text in 100+ languages, from BAAI's BGE-M3. Use for semantic search, RAG retrieval, clustering and deduplication.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- Qwen2.5 Coder 32B, code LLM APIagent-data-tools.revmesh2074.workers.devQwen2.5 Coder 32B, code LLM API. Chat with Alibaba's Qwen2.5 Coder 32B code model (Apache 2.0) through one paid HTTP call: send a prompt and an optional system prompt, get the answer, up to 1,024 output tokens. Also reachable as model "qwen-coder" on the OpenAI-compatible /v1/chat/completions. No account or provider key. Use when an agent wants this model by name.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- DeepSeek R1 reasoning model APIagent-data-tools.revmesh2074.workers.devDeepSeek R1 reasoning model API. Chat with DeepSeek's R1 reasoning model distilled into Qwen 32B (MIT) through one paid HTTP call: send a prompt and an optional system prompt, get the answer, up to 2,048 output tokens; its reasoning is removed from the answer. Also reachable as model "deepseek-r1" on the OpenAI-compatible /v1/chat/completions. No account or provider key. Use when an agent wants this model by name.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- LLM inference, large modelagent-data-tools.revmesh2074.workers.devLLM inference, large model. Send a prompt, get an answer from a larger open model: Llama 3.3 70B Instruct (default) or OpenAI gpt-oss-120b, with an optional system prompt, up to 1,024 output tokens and adjustable temperature. Same call as /ai/chat with a stronger model. Use when the 8B model is not enough: reasoning, drafting and Q&A.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- GPT-OSS 120B chat APIagent-data-tools.revmesh2074.workers.devGPT-OSS 120B chat API. Chat with OpenAI's open-weight gpt-oss-120b reasoning model (Apache 2.0) through one paid HTTP call: send a prompt and an optional system prompt, get the answer, up to 1,024 output tokens. Also reachable as model "gpt-oss-120b" on the OpenAI-compatible /v1/chat/completions. No account or provider key. Use when an agent wants this model by name.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- Chat completions (LLM)agent-data-tools.revmesh2074.workers.devOpenAI-compatible chat completions for agents, pay per request: Llama 4 Scout by default with function calling (tools, tool_calls), JSON mode and streaming; Llama 3.3 70B, gpt-oss-20b/120b, Qwen3 30B, Qwen2.5 Coder, Mistral Small 3.1 or DeepSeek R1 by model name. No account or API key; failed calls are not charged.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- Content moderation, safety checkagent-data-tools.revmesh2074.workers.devOpenAI-compatible moderation, pay per request: one input in, flagged and categories out (Llama Guard 3, 14 hazard categories mapped onto OpenAI names). No account or API key; failed calls are not charged.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- Chat completions (LLM)agent-data-tools.revmesh2074.workers.devOpenAI Responses API shape, pay per request: input text or messages, instructions and max_output_tokens in, one completed message and output_text out. Llama 4 Scout by default, Llama 3.3 70B or gpt-oss-120b by model name. No account or API key; failed calls are not charged.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- Content moderation, safety checkagent-data-tools.revmesh2074.workers.devContent moderation, safety check. Classify a text as safe or unsafe with Meta's Llama Guard 3 and name the hazard categories it falls into (violent and non-violent crimes, sexual content, child exploitation, hate, self-harm, weapons, privacy, defamation, elections and others; 14 in all). Up to 8,000 characters. Also available in the OpenAI moderation shape at /v1/moderations. Use to screen user messages, model outputs or content before an agent posts or acts on it.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- Mistral Small 3.1 chat APIagent-data-tools.revmesh2074.workers.devMistral Small 3.1 chat API. Chat with Mistral AI's Mistral Small 3.1 24B model (Apache 2.0) through one paid HTTP call: send a prompt and an optional system prompt, get the answer, up to 1,024 output tokens. Also reachable as model "mistral-small" on the OpenAI-compatible /v1/chat/completions. No account or provider key. Use when an agent wants this model by name.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- GPT-OSS 20B chat APIagent-data-tools.revmesh2074.workers.devGPT-OSS 20B chat API. Chat with OpenAI's open-weight gpt-oss-20b reasoning model (Apache 2.0) through one paid HTTP call: send a prompt and an optional system prompt, get the answer, up to 1,024 output tokens. Also reachable as model "gpt-oss-20b" on the OpenAI-compatible /v1/chat/completions. No account or provider key. Use when an agent wants this model by name.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- Qwen3 30B chat APIagent-data-tools.revmesh2074.workers.devQwen3 30B chat API. Chat with Alibaba's Qwen3 30B-A3B mixture-of-experts model (Apache 2.0) through one paid HTTP call: send a prompt and an optional system prompt, get the answer, up to 1,024 output tokens; its reasoning is removed from the answer. Also reachable as model "qwen3-30b" on the OpenAI-compatible /v1/chat/completions. No account or provider key. Use when an agent wants this model by name.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- OpenAI compatible embeddingsagent-data-tools.revmesh2074.workers.devOpenAI-compatible embeddings, pay per request: one input string in, a 1,024-dimension BGE-M3 vector out (multilingual, for search and RAG). No account or API key; failed calls are not charged.Livechecked Evidence 1/4x402x402 Bazaar2 payers
- LLM chat completion APIagent-data-tools.revmesh2074.workers.devLLM chat completion API. LLM chat completion and text generation: send a prompt (or an OpenAI messages array with tools and JSON mode) and get an answer from Meta's Llama 4 Scout, up to 1,024 output tokens, in a couple of seconds; OpenAI-compatible at /v1/chat/completions. Use for drafting, summaries, classification, reasoning steps and any quick LLM call without an AI provider account.Livechecked Evidence 1/4x402x402 Bazaar1 payer
- Text embeddings APIagent-data-tools.revmesh2074.workers.devText embeddings API: a 1,024-dimension vector for up to 4,000 characters of text in 100+ languages (BAAI BGE-M3), also OpenAI-compatible at /v1/embeddings. Use for semantic search, RAG retrieval, clustering, deduplication and similarity scoring.Livechecked Evidence 1/4x402x402 Bazaar1 payer
- LLM inference API, large modelagent-data-tools.revmesh2074.workers.devLLM inference API, large model. LLM inference with a large open model: send a prompt (optional system prompt, up to 1,024 output tokens) and get an answer from Llama 3.3 70B Instruct or OpenAI gpt-oss-120b in one call, with no provider account; OpenAI-compatible at /v1/chat/completions by model name. Use when a small model is not enough: reasoning, drafting, analysis and Q&A inside an agent workflow.Livechecked Evidence 1/4x402x402 Bazaar1 payer
- LLM pricing, compare AI modelagent-data-tools.revmesh2074.workers.devLLM pricing, compare AI model. Compare the API prices of about 450 LLMs from OpenAI, Anthropic, Google, Meta, Mistral, DeepSeek, Qwen and others: USD per million input and output tokens, context length, max output, modalities, and the cost of your call when you give token counts. Filter by name, provider, price cap, context or image input; sort by input, output or blended price. Source: OpenRouter's public model list. Use to pick the cheapest model that fits a job.Livechecked Evidence 1/4x402x402 Bazaar1 payer
- Claude pricingagent-data-tools.revmesh2074.workers.devClaude pricing for every Anthropic model: USD per million input and output tokens, context length, max output and modalities for Claude Haiku, Sonnet, Opus and the newer families, cheapest first, plus the cost of your call when you give token counts. Filter by name (q=sonnet), price cap, context or image input. Source: OpenRouter's public model list. Use to pick a Claude model for a job or to estimate what a prompt will cost before sending it.Livechecked Evidence 1/4x402x402 Bazaar1 payer
- GPT pricingagent-data-tools.revmesh2074.workers.devGPT pricing for every OpenAI model: USD per million input and output tokens, context length, max output and modalities for GPT, o-series and open-weight models, cheapest first, plus the cost of your call when you give token counts. Filter by name (q=gpt-5), price cap, context or image input. Source: OpenRouter's public model list. Use to pick an OpenAI model for a job or to estimate what a prompt will cost before sending it.Livechecked Evidence 1/4x402x402 Bazaar1 payer
- MiniMax pricingagent-data-tools.revmesh2074.workers.devMiniMax pricing for every MiniMax model: USD per million input and output tokens, context length, max output and modalities for MiniMax M3 and the other MiniMax models, cheapest first, plus the cost of your call when you give token counts. Filter by name (q=m3), price cap, context or image input. Source: OpenRouter's public model list. Use to pick a MiniMax model for a job or to estimate what a prompt will cost before sending it.Livechecked Evidence 1/4x402x402 Bazaar1 payer
- Grok pricingagent-data-tools.revmesh2074.workers.devGrok pricing for every xAI model: USD per million input and output tokens, context length, max output and modalities for Grok 4.x and the other xAI models, cheapest first, plus the cost of your call when you give token counts. Filter by name (q=grok-4), price cap, context or image input. Source: OpenRouter's public model list. Use to pick a Grok model for a job or to estimate what a prompt will cost before sending it.Livechecked Evidence 1/4x402x402 Bazaar1 payer