Public MCP now supports a new multi-query signature with advanced AI search settings. Configure search parameters such as searchable attributes, ranking, and filters independently of index settings, and update them without recreating the MCP. Click here to learn more.
AI Assist now understands your configuration and uses this to provide advice that's tailored and relevant. A question like “Why do I have a high no-results rate?” will be met with targeted guidance on how to change your current set-up. Assist will also provide links to navigate you to relevant parts of the Algolia platform. This allows you to quickly find the relevant solution needed to take action on an Assist conversation. Assist is aware of your application’s current subscription tier and Algolia release version, and will only direct you to features you can access.
Agent Studio is now generally available, providing a managed platform for building, deploying, and operating AI agents grounded in Algolia data. Customers can configure model providers, connect search and recommendation tools, add safety controls, and monitor conversations through a single API and dashboard. This reduces the complexity of building production-ready AI experiences while providing a consistent, scalable foundation for agent development. Click here to learn more.
Agent Studio now generally supports Model Context Protocol (MCP) servers, allowing AI agents to securely connect to external tools and services through a standardized interface. Customers can extend agent capabilities with approved third-party tools while controlling which tools are available and requiring human approval for sensitive actions. This makes it easier to integrate existing systems into AI workflows without building custom integrations. Click here to learn more.
Algolia CLI v1.8.1 introduces updates that improve automation, security, and AI agent interoperability from the terminal. New capabilities include schema introspection with algolia describe, structured JSON and NDJSON output, expanded dry-run validation for mutation commands, OAuth PKCE authentication with scoped user permissions, and input validation for malformed control characters. The release also adds crawler authentication through the dashboard with algolia auth crawler and a new compositions command group for managing compositions and composition rules directly from the CLI. These updates help developers and AI agents interact with Algolia more safely, predictably, and efficiently in automated workflows. Click here to learn more.
Safety Controls in Agent Studio introduce guardrails for deploying agents in production. Configure global and per-IP rate limits to handle spikes, set limits on tokens, steps, and conversation depth to manage cost, and restrict access using domain allowlists. This helps prevent abuse, reduce unexpected spend, and ensure agents are only accessible from approved environments.
The Algolia Productivity MCP now supports Claude Code, Cursor, VS Code, Gemini CLI, and Codex. Developers can connect to Algolia (via Dashboard OAuth) directly from their preferred Al coding environment and query Algolia without switching context. Each AI assistant is recognised by the MCP and matched against a redirect URI, without needing to enter a Client ID. Click here to learn more.
Agent Studio now includes a dedicated search settings panel, letting teams configure search parameters specifically for their agents - separate from existing index settings. Defaults (hits per page, controlled attributes, facets) are set based on evaluation findings and applied automatically when connecting a new index. All settings are fully customizable.
Agent Studio's search tool has been upgraded with improved relevance, faster response times, and reduced cost per query. Agents now benefit from more accurate, context-aware results across a wider range of query types. AI-generated tool descriptions also help agents select and invoke the right search tool at the right time, improving overall agent reasoning quality.
A new Guardrails configuration in the Safety Controls tab allows defining custom categories to filter harmful or off-topic content across input, output, or both. Each category includes a description, examples, and an optional fallback response, helping teams control how agents handle sensitive or irrelevant queries. This improves response quality, reduces risk, and ensures interactions stay aligned with the intended use case. Click here to learn more.
