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Launch HN: Strata (YC X25) – One MCP server for AI to handle thousands of tools

133 points wirehack | 2 comments | 23 Sep 25 14:52 UTC | HN request time: 0s | source

Hey HN! We are Klavis AI (https://www.klavis.ai/) and we're launching Strata, one open-source MCP server that helps AI agents use thousands of API tools without getting overwhelmed. Instead of showing all available tools at once, Strata reveals them step-by-step based on what the AI actually needs.

As a former Senior SWE on Google Gemini 's tool use team, I saw firsthand how AI would struggle with tools. If you've built AI agents, you've likely hit the same walls: (1) AI agents struggle to pick the right API from hundreds of options. (2) Tool descriptions and info consume massive token budgets. (3) Most servers cap at 40~50 tools to avoid these problems, limiting what you can build.

Instead of flooding the AI with everything upfront, Strata works like a human would. It guides the AI agents to discover relevant categories, then lists available actions in those categories. It relies on LLMs’ reasoning to drill down progressively to find the exact tool needed. Here are some examples:

Github query: "Find my stale pull requests in our main repo"

Strata: AI model identifies GitHub → Shows categories (Repos, Issues, PRs, Actions) → AI selects PRs → Shows PR-specific actions -> AI selects list_pull_requests → Shows list_pull_requests details -> Executes list_pull_requests with the right parameters.

Jira query: "Create a bug ticket in the 'MOBILE' project about the app crashing on startup."

Strata: AI identifies Jira → Shows categories (Projects, Issues, Sprints) → AI selects Issues → Shows actions (create_issue, get_issue) → AI selects create_issue → Shows create_issue details → Executes with correct parameters.

Slack query: "Post a message in the #announcements channel that bonus will be paid out next Friday."

Strata: AI identifies Slack → Shows categories (Channels, Messages, Users) → AI selects Messages → Shows actions (send_message, schedule_message) → AI selects send_message → Shows send_message details → Executes with correct parameters.

This progressive approach unlocks a huge advantage: depth. While most integrations offer a handful of high-level tools, Strata can expose hundreds of granular features for a single app like GitHub, Jira, etc. Your AI agent can finally access the deep, specific features that real workflows require, without getting lost in a sea of options.

Under the hood, Strata manages authentication tokens and includes a built-in search tool for the agent to dig into documentation if it gets stuck.

On the MCPMark https://mcpmark.ai/leaderboard/mcp, Strata achieves +15.2% higher pass@1 rate vs the official GitHub server and +13.4% higher pass@1 rate vs the official Notion server. In human eval tests, it hits 83%+ accuracy on complex, real-world multi-app workflows.

Here is a quick demo to watch Strata navigate a complex workflow with multiple apps, automatically selecting the right tools at each step: https://www.youtube.com/watch?v=N00cY9Ov_fM.

You can connect to any external MCP Server into Strata, and we have an open source version for it: https://github.com/Klavis-AI/klavis.

For team or production use with more features, visit our website: https://www.klavis.ai. Add Strata to Cursor, VS Code or any MCP-compatible application with one click. You can also use our API to easily plug in Strata to your AI application.

We look forward to your comments. Thanks for reading!

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deepdarkforest ◴[23 Sep 25 17:08 UTC] No.45349914[source]▶
1. Interesting approach, but the pricing seems 1-2 orders of magnitude too expensive. For your example for slack, It contains 4 calls for an action. Pricing shows 100 dollars per 10k cals, so 1 cent per call. This means, for an agent that lets say does 4 actions, so and your examples show at least 3-4 api calls per action , it's already 12 cents? Similar tools like composio.dev have 200k calls for 29 dollars, so around 70x cheaper (both for the cheapest tier). Even with needing only 1 call for subsequent calls, 1 cent per single api call sounds wrong, at least for our use case it does not economic sense to pay 5-10 cents on top of llm costs on every user query. Apologies if I'm missing something!

2. Could this not be replicated by others by just handmaking a fuzzy search tool on the tools? I think this is the approach that will win, even with rag for lets say 10k plus tools maybe in the future, but not sure how much differentiation this is in the long term, i've made this search tool myself a couple of times already

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wirehack ◴[23 Sep 25 17:11 UTC] No.45349971[source]▶
1. Hi! We noticed this for Strata as well so we are ONLY counting the execute_action in Strata. This means the fee is the same as using the traditional, flat approaches. In other words, the 3 previous calls does not cost you anything!

2. I think the main drawback of search method is like giving a human lots of tools/APIs but you can ONLY access them via a search interface. This feels weird and should be improved. For our approaches, the step by step methods allow you to see what categories/actions are available. We also provide a documentation search so that you get the best out of both worlds.

replies(2): >>45350032 #>>45350069 #
deepdarkforest ◴[23 Sep 25 17:17 UTC] No.45350069[source]▶
1. Oh okay great, maybe clarify it in the pricing page? That mcp server call means just execute. But its' still 10x more expensive right?

2. From what i understand it's just nested search right? It is not anything different, if you do flat or embedding search or fuzzy/agentic nested is a choice for sure, but Im just saying not sure how defensible this is, if all other mcp competitors or even users themselves put in a nested search tool

replies(1): >>45350139 #
wirehack ◴[23 Sep 25 17:22 UTC] No.45350139[source]▶
1. Sure, we will clarify that in the pricing page, thank you! As you can see from our evaluation, we are much better than official MCP servers. I think people care more about getting things done correctly. Otherwise, you waste all the model tokens for nothing. We do have enterprise deals where we can work out a customized pricing plan for your specific use case. Come talk to us if you are interested.

2. One VERY important distinction is that the model is doing the "search" here, not some RAG algorithm or vector database. Therefore, as the model becomes smarter, this approach will be more accurate as well.

replies(1): >>45350495 #
1. deepdarkforest ◴[23 Sep 25 17:51 UTC] No.45350495[source]▶
1. I was not talking about official MCP servers, those are often even free. Im talking about pricing of other devtools for aggregating tools/mcp's. I think this is an obvious space to build i agree, i just worry about differentiation. Its a search space not as big as web search, or complex (order doesnt matter).

2. Yes, i see, this is what i meant by agentic search. Essentially is a tiny subagent, taking list of tools in and out the relevant ones. Still implementable in 5 mins. But i guess if the experience is very smooth enterprise might pay?

replies(1): >>45350575 #
2. wirehack ◴[23 Sep 25 17:57 UTC] No.45350575[source]▶
1. Yes I agree. To be honest we are a young company (as you can tell we are from YC X25), so we are still figuring out the pricing. But thank you for the feedback and sharing your thoughts.

2. Yes the idea is not complex once you understand it. But there are some nuances we found along the way and supporting more integrations are always important but requires engineering efforts. Thank you!