AI agents generate structured data constantly: tool outputs, conversation logs, scraped content, task results. Sprigr gives your agent a simple REST API to store any JSON and search it instantly. No database setup, no schema design, no backend code.
Cloud-hosted: data persists across runs and machines. Schema-free JSON: store anything, change shape anytime. Built-in full-text search with no extra infrastructure. REST API works from any language, any framework. Ready in 60 seconds, no provisioning, no migrations.
You focus on the work. Sprigr runs the paperwork.
Every feature designed around the reality of AI agent data patterns.
No tables to create, no columns to define. Push a flat key-value object today, a deeply nested structure tomorrow. Sprigr indexes every field automatically.
Find records by content, not just IDs. Typo-tolerant keyword search plus optional hybrid semantic search that finds results by meaning, even when the exact words don't match.
Combine text search with exact-match filters on any JSON field. Query status:complete, agent_id:agent-7, or source:web-scrape alongside free-text terms.
Create separate indexes for different agents, users, or data types. Each index is isolated with no data bleed between tenants. Spin up a new index with a single API call.
Standard REST endpoints work with curl, fetch, requests, or any HTTP client. For agents built on the Model Context Protocol, Sprigr also ships an MCP server for native tool integration.
Pay per records stored, not per query. No surprise bills when your agent runs a thousand searches in a loop. Free tier included for prototyping and small projects.
Three steps from raw agent output to searchable cloud storage.
Create a free account and generate an API key. Each key is scoped to an index, a dedicated namespace for your agent's data.
Send records to the Sprigr REST API with a single POST request. No schema to define, no migrations to run. If it's valid JSON, Sprigr stores it and indexes it for search.
Fetch records by ID for exact lookups, or use full-text search to find records by content. Add facet filters to narrow results by any field in your JSON.
Push JSON: POST /1/indexes/agent-data/batch with your records. Search it: POST /1/indexes/agent-data/query with query and filters. Retrieve by ID: GET /1/indexes/agent-data/objects/task-result-001. The same calls work from Python, JavaScript, Go, or any language with an HTTP library.
Any valid JSON. Conversation history, tool outputs, scraped web pages, task results, extracted facts, embeddings, user preferences. The API is schema-free, so records can have completely different shapes within the same index. If your agent produces structured data, Sprigr can store and search it.
No. Sprigr is schema-free. Push a record with any JSON structure and it gets indexed automatically. You can change the shape of your records over time without migrations. Fields that appear in some records and not others just show up empty in search results.
Three ways: fetch records by their objectID for exact lookups, run full-text search queries with typo tolerance, or combine free-text search with facet filters on any JSON field. All three work through the same REST API and return results in milliseconds.
Yes. Multiple agents can read and write to the same index using the same API key, or you can give each agent its own API key. Use facet filters (for example, agent_id:agent-7) to keep each agent's records separate while still allowing cross-agent queries when needed.
The REST API works with any HTTP client: curl, fetch, requests, axios, whatever you already use. For Model Context Protocol agents, we provide an MCP server (@sprigr/mcp-server) that exposes Sprigr as native tools in Claude Desktop, Claude Code, and other MCP clients.
Free forever for small projects. Paid plans from $49/mo.