fastn.ai
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Fastn is an AI infrastructure platform that connects AI agents to the tools they need through a single endpoint. Instead of building and maintaining a separate integration for every service an agent touches, Fastn routes connectors like Slack, Notion, Gmail, and custom APIs through one MCP-based gateway, handling authentication and workflow orchestration along the way. Key capabilities:
Unified gateway โ one Model Context Protocol endpoint exposes your whole toolset to any agent Full integration lifecycle โ AI agents build, test, and keep connectors running as upstream APIs change Workflow orchestration โ chain multi-step automations across connected tools Built-in auth โ OAuth and credential handling managed for you Embeddable โ let your own customers configure their integrations inside your product Enterprise-ready โ SOC 2 Type II, role-based access, SSO/SAML, and configurable data residency at scale
Fastn is priced by connected customer accounts rather than by connector count, so cost tracks the customers you actually serve.
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fastn.ai's answer
Fastn treats the entire integration lifecycle as something AI agents handle, not engineers. Rather than building and maintaining a connector for every tool an AI agent needs, fastn exposes connectors like Slack, Notion, Gmail, and custom APIs through a single MCP-based gateway, with authentication and workflow orchestration built in. Its agents don't just build integrations, they test and keep them running as upstream APIs change. Pricing is based on connected customer accounts rather than connector count, so cost tracks the customers served, not the integrations maintained.
fastn.ai's answer
Most integration tools leave you with a backlog: every new connector is an engineering ticket, and breakages become maintenance work. Fastn shifts that to AI agents that build, test, and proactively maintain connections, adapting before APIs break rather than after. The single-endpoint MCP gateway means an agent gains access to a whole toolset without per-connector plumbing, and the embeddable model lets software companies offer self-serve integrations inside their own products. For teams building AI agents and automations, that means less time on glue code and faster validation of new use cases.
fastn.ai's answer
Fastn is built for developers and product teams building AI agents, automations, and agentic applications, particularly software companies that want to offer customer-facing integrations inside their own products without growing an integrations engineering team. It serves both individual builders prototyping agentic systems and larger organizations that need enterprise-grade security, monitoring, and scale.
Found the embedding feature easy to use with a simple URL add on, didnt need to focus so much on building an entire layer
Based on our record, opencode seems to be more popular. It has been mentiond 67 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Https://opencode.ai/ OpenCode was the first agent harness I used, and I have always like it. You can configure a wide variety of providers, but it's open source and has a number of core contributors. The other opinionated option is Pi (the Pi agent harness). This is a great lightweight option and also supports a number of providers. You can also use local model servers. - Source: Hacker News / 24 days ago
OpenCode with GLM 5.2 wrote custom Emacs Lisp to pinpoint within the file where the missing or extra bracket could be. It rewrote the custom code to check various parts of the file. Each of those is a tool use and many, many tokens burned. The next step is to turn those custom scripts written by the AI agent into a tool to speed up the process, or a skill that shows how to use other tools to speed up the process. - Source: dev.to / 26 days ago
I gave GLM-4.5-Air (106B, open weights) 12 coding tasks through opencode on my RTX 3090. It scored 0% โ never edited a single file. - Source: dev.to / 27 days ago
Set up your stations. I work in two Ghostty terminals. The left side is for planning and viewing, the right for synchronous agents running through OpenCode. - Source: dev.to / about 1 month ago
If you want to try it yourself: grab OpenCode, point it at OpenRouter, select GLM 5.2, and give it a real task instead of a benchmark. The z.ai docs have the rest of the details. - Source: dev.to / about 1 month ago
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