Sutra

Private, provider-agnostic memory and reusable skills shared across AI agents through MCP.

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What it can do

  • Read Context: Load the user's shared Sutra identity context. Call this before answering broad questions about the user's preferences, history, projects, or prior decisions. The result can contain sens
  • Write Observation: Save one durable memory only after the user clearly asks or agrees to save it. Use for stable preferences, decisions, corrections, working patterns, or project facts. Do not store i
  • Search Memory: Search for targeted memories using short, specific keywords. This uses case-insensitive plain-text matching. For broad personal questions, call read_context first. If this returns no re

What data it sees

Do you need an account

No: the server works without sign-in

Private, provider-agnostic memory and reusable skills shared across AI agents through MCP.

How to connect

How to connect Sutra to Claude

The server address to paste into Claude settings:

https://sutra--sutra.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect Sutra to ChatGPT

The server address to paste into ChatGPT settings:

https://sutra--sutra.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect Sutra to Cursor

The server address to paste into Cursor settings:

https://sutra--sutra.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (10)

Raw names from tools/list. Only developers need these.

read_contextLoad the user's shared Sutra identity context. Call this before answering broad questions about the user's preferences, history, projects, or prior decisions. The result can contain sensitive personal data, so use only the details needed to answer the user's current request. For a targeted lookup, use search_memory instead.
write_observationSave one durable memory only after the user clearly asks or agrees to save it. Use for stable preferences, decisions, corrections, working patterns, or project facts. Do not store inferred traits, secrets, transient conversation, or information the user did not authorize Sutra to retain.
search_memorySearch for targeted memories using short, specific keywords. This uses case-insensitive plain-text matching. For broad personal questions, call read_context first. If this returns no results, call read_context before concluding that nothing relevant is known. Do not use this to enumerate all user data; use export_all only when the user explicitly requests an export.
get_clusterGet memories and metadata for one known project cluster. Use list_clusters first if the cluster name is unknown. Do not use this for a keyword search across clusters; use search_memory instead.
list_clustersList project clusters with descriptions and memory counts. Use this to discover a cluster name before get_cluster. It does not return the memories stored inside each cluster.
export_allExport all user memories as structured JSON for data portability. Call only when the user explicitly requests a complete export or backup. This returns potentially sensitive data from every cluster; do not call it merely to answer a question, search memory, or inspect one cluster.
list_skillsList reusable skills the user has explicitly enabled in Sutra. Use this to discover an enabled skill slug before get_skill. It returns metadata, not the skill instructions or resource contents.
get_skillLoad an enabled SKILL.md and its supporting resource index. Use after list_skills identifies a relevant skill. Load individual resources with get_skill_resource only when the skill instructions require them.
get_skill_resourceRead one supporting file from an enabled Sutra skill. Use only for a path listed by get_skill and only when needed for the current task. Do not guess paths or load every resource preemptively.
upload_skillUpload a SKILL.md and optional text resources when the user explicitly asks. Do not create or upload a skill based on inference or without clear authorization. The new version remains disabled until the user enables it in the dashboard.