# Minns Memory Layer

## Docs

- [Get claim](https://docs.minns.ai/api-reference/claims/get-claim.md): Retrieve a specific claim by its ID.
- [List claims](https://docs.minns.ai/api-reference/claims/list-claims.md): List all extracted facts (claims) from processed events.
- [Process embeddings](https://docs.minns.ai/api-reference/claims/process-embeddings.md): Manually trigger embedding generation for pending claims.
- [Search claims](https://docs.minns.ai/api-reference/claims/search-claims.md): Semantic search over extracted claims — find soft facts like user preferences and intent.
- [Event types reference](https://docs.minns.ai/api-reference/events/event-types.md): Complete reference for all six EventType variants — Action, Observation, Cognitive, Communication, Learning, and Context.
- [Get episodes](https://docs.minns.ai/api-reference/events/get-episodes.md): Retrieve completed episodes detected by the system.
- [Get events](https://docs.minns.ai/api-reference/events/get-events.md): Retrieve recent events from the database.
- [Process event](https://docs.minns.ai/api-reference/events/process-event.md): Ingest a new event and trigger automatic graph construction, episode detection, and claim extraction.
- [Analytics](https://docs.minns.ai/api-reference/graph/analytics.md): Advanced graph analytics — connected components, clustering, modularity, and learning metrics.
- [Centrality](https://docs.minns.ai/api-reference/graph/centrality.md): Retrieve node centrality scores — importance ranking across multiple metrics.
- [Communities](https://docs.minns.ai/api-reference/graph/communities.md): Retrieve detected communities using the Louvain algorithm.
- [Graph by context](https://docs.minns.ai/api-reference/graph/context-graph.md): Retrieve a subgraph centered around a specific context fingerprint.
- [Get graph](https://docs.minns.ai/api-reference/graph/get-graph.md): Retrieve the graph structure — nodes and edges — for visualization and analysis.
- [Index stats](https://docs.minns.ai/api-reference/graph/indexes.md): Retrieve statistics on property indexes — hits, misses, and query counts.
- [System stats](https://docs.minns.ai/api-reference/graph/stats.md): High-level system statistics — total events, nodes, episodes, and processing performance.
- [API overview](https://docs.minns.ai/api-reference/introduction.md): The Minns Memory Layer REST API — base URL, authentication, conventions, and system limits.
- [Search by context](https://docs.minns.ai/api-reference/memory/context-search.md): Find memories relevant to the current task by matching goals and environment against past episodes.
- [Get agent memories](https://docs.minns.ai/api-reference/memory/get-agent-memories.md): Retrieve long-term memories for a specific agent.
- [Get agent strategies](https://docs.minns.ai/api-reference/strategies/get-strategies.md): Retrieve learned behavioral strategies for a specific agent.
- [Find similar strategies](https://docs.minns.ai/api-reference/strategies/similar.md): Find strategies similar to a given set of goals or tools — share wisdom across agents.
- [Action suggestions](https://docs.minns.ai/api-reference/strategies/suggestions.md): The Policy Guide endpoint — ask 'What should the agent do next?'
- [Health check](https://docs.minns.ai/api-reference/system/health.md): Check server status, version, uptime, and engine health metrics.
- [Types & primitives](https://docs.minns.ai/api-reference/types.md): Complete reference for all primitive types, the Event structure, EventContext, and MetadataValue used across the API.
- [Authentication](https://docs.minns.ai/authentication.md): Authenticate with the Minns Memory Layer API using project API keys, and manage key rotation from the project page.
- [Core concepts](https://docs.minns.ai/concepts.md): Understand the building blocks of Minns Memory Layer — Events, Episodes, Goals, Memory, Claims, and Strategies.
- [Building a chat agent](https://docs.minns.ai/guides/building-a-chat-agent.md): A deep dive into intent-driven agent architecture — from theory to a fully working chat agent with memory, strategies, and knowledge extraction.
- [Integration examples](https://docs.minns.ai/guides/integration-examples.md): End-to-end examples showing how to integrate Minns Memory Layer into real agent workflows using the minns-sdk.
- [Query selection guide](https://docs.minns.ai/guides/query-selection.md): Minns Memory Layer provides five distinct search methods. Learn which one to use for every situation.
- [Use case recipes](https://docs.minns.ai/guides/use-case-recipes.md): Ready-to-adapt patterns for customer support bots, research agents, e-commerce assistants, IoT monitoring, and more — all powered by minns-sdk.
- [Minns Memory Layer](https://docs.minns.ai/index.md): The graph-native database built for agentic AI workflows. Store events, form memories, extract knowledge, and learn strategies — automatically.
- [Quickstart](https://docs.minns.ai/quickstart.md): Get Minns Memory Layer running and log your first event in under 5 minutes.
- [Event builder](https://docs.minns.ai/sdk/event-builder.md): Use the fluent EventBuilder API to construct rich events with actions, observations, goals, causality, and context.
- [Installation & setup](https://docs.minns.ai/sdk/installation.md): Install the minns-sdk and configure the Minns Memory Layer client for your application.
- [Memory & strategies](https://docs.minns.ai/sdk/memory-strategies.md): Query agent memories, search claims, retrieve strategies, and get action suggestions via the SDK.
- [Security & resilience](https://docs.minns.ai/sdk/security.md): Built-in protections against circular references, prototype pollution, oversized payloads, and queue overflow.
- [Sidecar intent parsing](https://docs.minns.ai/sdk/sidecar.md): Extract structured intents from LLM responses locally — no network round-trips required.

## OpenAPI Specs

- [openapi](https://docs.minns.ai/openapi.json)