Alternatives
Products that do what We let agents use APIs to find out if they can actually...do things? does
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We run superglue, an OSS agentic integration platform. Last week I talked to a founder of another YC startup. She found a use case for our CLI that we hadn't officially launched yet. Her problem: customers wanted to create Opps in Salesforce from inside the chat in her app. We kept seeing this pattern: teams build agents and their users can perfectly describe what they want: "pull these three objects from Salesforce and push to nCino when X condition is true", but translating that into a generalized hard-coded tool the agent can call is a lot of work and does not scale since the logic is…
Apr 2026 · docs.superglue.cloud
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Hi HN, we’re Stefan and Adina, and we’re building superglue (https://superglue.cloud). superglue allows you to connect to any API/data source and get the data you want in the format you need. It’s an open-source proxy server which sits between you and your target APIs. Thus, you can easily deploy it into your own infra. If you’re spending a lot of time writing code connecting to weird APIs, fumbling with custom fields in foreign language ERPs, mapping JSONs, extracting data from compressed CSVs sitting on FTP servers, and making sure your integrations don’t break when…
2025 · github.com
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Our most accurate Search API for AI agents.
Jul 2026 · docs.firecrawl.dev
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This project (Agents Observe) started as an exploration into building automation harnesses around claude code. I needed a way to see exactly what teams of agents were doing in realtime and to filter and search their output. A few interesting learnings from building and using this: - Claude code hooks are blocking - performance degrades rapidly if you have a lot of plugins that use hooks - Hooks provide a lot more useful info than OTEL data - Claude's jsonl files provide the full picture - Lifecycle management of MCP processes started by plugins is a bit kludgy at best The biggest takeaway is…
Apr 2026 · github.com
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com
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