Klavis Strata
About
One MCP server for AI agents to use any tools reliably at any scale
Details
- Author
- Unknown
- Categories
- Other, AI, Automation, API
Jump to
- Discover relevant actions— Ask your AI to find matching categories or actions across servers usingdiscover_server_categories_or_actionsbased on your intent.
- Explore category capabilities— Retrieve all action names within specific categories viaget_category_actionsto understand available operations.
- Inspect action schemas— Get full parameter details for any action withget_action_details, including required and optional fields.
- Execute operations— Run actions with parameters throughexecute_action, optionally filtering response fields or limiting output size.
- Search documentation— Usesearch_documentationwith targeted keywords to find relevant endpoints when discovery results are insufficient.
- Resolve authentication issues— Handle auth failures during execution by getting auth URLs or saving credentials viahandle_auth_failure.
One MCP server for AI agents to use tools progressively at any scale
Stratais one MCP server that guides AI agents use tools reliably at any complexity, instead of overwhelming them with everything at once, it was designed by thinking human interacting with tools, solving the three major problems that plague AI agents today:
- Tool Overload: Too many tools cause LLM choice paralysis
- Context Overload: Long tool lists blow up token counts and costs
- Coverage Gap: Most servers are stuck at 40~50 tools, limiting what you can build
You can use Strata via our](https://mintcdn.com/klavisai/7Siw7A5JJSHURM5d/images/concepts/strata_hero.png?fit=max&auto=format&n=7Siw7A5JJSHURM5d&q=85&s=b581fdb821699a32b260d124789396bd)website,API, or evenopen sourceon your own data!
Watch this video tutorial for a complete understanding of how Strata works:
Check out thisshared Claude conversationto see Strata in action!
1. Discover Server Categories or Actions
discover_server_categories_or_actions- find relevant categories or actions based on user intent. No semantic search!
If detail level is 'categories_only', the details will be a list of category names only. Next step prefer to use get_category_actions tool to get the actions for the categories.
If detail level is 'full_details', the details will be a list of category names with their actions details included. This happens when the server has only a few actions. Next step prefer to use execute_action tool to execute the actions.
If detail level is 'categories_and_actions', the details will be a list of category names and action names. This happens when using external tools. Next step prefer to use get_action_details tool to get the details of the actions.
- user_query(string, required): Natural language user query to filter results.
- server_names(array, required): List of server names to discover categories or actions.
get_category_actions- retrieve all action names within specified categories.
- category_names(array, required): List of categories to get actions for
get_action_details- get full schema and parameters for a specific action.
- category_name(string, required): The name of the category
- action_name(string, required): The name of the action/operation within the category
execute_action- run actions with parameters and get results.
- server_name(string, required): The name of the server
- category_name(string, required): The name of the category to execute the action for
- action_name(string, required): The name of the action/operation to execute
- path_params(string, optional): JSON string containing path parameters for the action
- query_params(string, optional): JSON string containing query parameters for the action
- body_schema(string, optional, default: "{}"): JSON string containing request body for actions
- include_output_fields(array, optional): Optional but strongly recommended when you know the response_schema of this action from previous tool calls: Array of field paths to include in the response. Only these fields will be returned. Use dot notation for nested fields (e.g., "author.displayName").
- maximum_output_characters(integer, optional): Optional: Maximum number of characters to return in the response. If the response exceeds this limit, it will be truncated. Prefer include_output_fields over this.
search_documentation- find relevant information only when needed.
- query(string, required): Search keywords that match API documentation terms. Best practices: (1) Use resource names like 'users', 'projects', 'files', (2) Add actions for precision like 'user create' or 'project delete', (3) Avoid filler words like 'how to', 'show me', 'all the' - focus on the core terms that appear in endpoint names and descriptions.
- server_name(string, required): Name of the server to search within.
- max_results(integer, optional, default: 10, minimum: 1, maximum: 50): Number of results to return. Default: 10
handle_auth_failure- handle authentication only when needed.
- server_name(string, required): The name of the server that failed authentication during execute_action
- intention(string, required, enum: ["get_auth_url", "save_auth_data"]): Use 'get_auth_url' when execute_action fails with authentication errors to get authentication instructions. Use 'save_auth_data' when user provides authentication credentials after an authentication failure.
- auth_data(object, optional): Authentication data provided by user after an authentication failure (e.g.,{"token": "...", "api_key": "..."}). Only used with 'save_auth_data' intention when resolving authentication failures.
- MCPMark Benchmark: Achieves+15.2% higher pass@1 ratevs the official GitHub server and+13.4% higher pass@1 ratevs the official Notion server. (Source)
- Human Evaluation: Hits83%+ accuracyacross >2k real world queries evaluation sets
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