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Hindsight

by vectorize-io

Adds long-term Hindsight memory to agents through retain, recall, and reflect operations.

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Install Hindsight

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "vectorize-io-hindsight": {
      "command": "npx",
      "args": [
        "-y",
        "@vectorize-io/hindsight-coding-agents"
      ],
      "env": {
        "HINDSIGHT_API_LLM_API_KEY": "YOUR_VALUE_HERE",
        "HINDSIGHT_API_LLM_PROVIDER": "YOUR_VALUE_HERE",
        "HINDSIGHT_DB_PASSWORD": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

vectorize-io/hindsight connects MCP-compatible agents to Hindsight, a long-term memory system designed to help agents learn over time. Its core operations retain information, recall relevant memories, and reflect on queries with a disposition-aware response. Use it for agents that need persistent knowledge beyond a single conversation, with Hindsight available through self-hosted, embedded, or managed deployments.

Use cases

  • Store user facts across conversations
  • Recall relevant project knowledge for an agent
  • Generate responses from accumulated memory
  • Give coding agents persistent context
  • Maintain separate memory banks for applications

Key features

  • Long-term agent memory
  • Retain, recall, and reflect operations
  • Memory-bank organization
  • Self-hosted and managed deployment options
  • Support for hosted and local LLM providers

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

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Recent health check succeeded.

30/31 checks healthy over the last 78d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

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Scanned 6d ago via OSV.dev · @vectorize-io/hindsight-coding-agents (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars54kStargazers on the source repository.
Last commitTodayMost recent push to the default branch.
Directory activity15 viewsConfig copies, upvotes, and views on AllMCPs.

How Hindsight works

What vectorize-io/hindsight MCP server does

vectorize-io/hindsight exposes Hindsight’s long-term memory capabilities to AI agents through MCP. Hindsight is intended for agents that need to accumulate knowledge and use it in later interactions, rather than only retrieve recent conversation history.

The memory system organizes information into memory banks. An agent can add observations, search previously retained information, or ask Hindsight to generate a response based on what it knows. This makes the server relevant to assistants, coding agents, and other applications that need persistent context across sessions.

How it works

Hindsight centers on three operations:

  • Retain stores information in a selected memory bank.
  • Recall searches a bank for memories related to a query.
  • Reflect generates a response using the bank’s accumulated knowledge and the query’s context.

For example, an agent can retain a fact such as a person’s employer, recall what that person does later, and use reflect to produce a more complete answer. Memory is kept in Hindsight rather than limited to the current agent conversation.

The underlying Hindsight service can run with an embedded database, Docker, a separately managed PostgreSQL database, Kubernetes, or Hindsight Cloud. Clients can also use the HTTP API directly. Hindsight supports Python, Node.js/TypeScript, Go, and command-line clients in addition to MCP-based access.

Setup and configuration

Self-hosted deployments can be started with Docker, installed with pip install hindsight-api, or deployed with the published Helm chart. The quick-start configuration uses an LLM provider and API key, such as HINDSIGHT_API_LLM_API_KEY with OpenAI. The service exposes an API on port 8888 in the Docker example and a UI on port 9999.

Hindsight supports hosted providers, local runtimes, OpenAI-compatible endpoints, and gateway options. Provider configuration is selected through HINDSIGHT_API_LLM_PROVIDER. Hindsight Cloud provides a hosted endpoint at https://api.hindsight.vectorize.io for deployments that do not run the service locally.

MCP clients named for the project include Claude Code and Cursor. The repository also describes support for Windows, Linux, macOS, air-gapped setups, and multiple deployment models.

Tools and capabilities

  • Retain facts, events, and other information in a memory bank.
  • Recall relevant stored memories with a natural-language query.
  • Reflect over memory to generate a disposition-aware response.
  • Maintain persistent agent knowledge across conversations.
  • Use hosted or self-managed Hindsight infrastructure.
  • Connect through Hindsight’s supported API clients and service endpoints.

Limitations and notes

Hindsight requires an LLM provider configuration for its memory service, unless using a supported subscription-based provider or local model setup. Storage and deployment choices affect how the service is operated: self-hosted installations require infrastructure management, while Hindsight Cloud uses a hosted endpoint.

The system is designed around Hindsight memory banks and its retain, recall, and reflect workflow. Agents that only need short-lived conversational context may not need a persistent memory service.

Read the full README View source on GitHub

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Frequently Asked Questions about Hindsight

vectorize-io/hindsight is an MCP server that connects AI agents to Hindsight, a long-term memory system. Its main tools support retaining information, recalling stored memories, and reflecting on a query to produce a disposition-aware response. Use it when an agent needs persistent knowledge across conversations.

Install the underlying Hindsight service with Docker, `pip install hindsight-api`, Helm, or use Hindsight Cloud. Docker and bare-metal examples require an LLM provider configuration such as `HINDSIGHT_API_LLM_API_KEY`; the service API is available on port 8888 in the Docker quick start.

It supports retain, recall, and reflect. Retain stores information in a memory bank, recall searches that bank, and reflect generates a response using the bank’s accumulated knowledge and the query.

Yes, Cursor is named as a supported coding-agent integration. Claude Code is also named, and the project describes the documentation skill as working with Cursor and other AI coding assistants.

Yes, Hindsight Cloud provides a managed option with a hosted API endpoint. Hindsight also offers an embedded Python mode through the `hindsight-all` package, which runs without a separate server process.

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