core

Recall past conversations and user preferences with searchable long‑term memory.

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What it can do

  • Memory Ingest: Store conversation in memory for future reference. USE THIS TOOL: At the END of every conversation after fully answering the user. WHAT TO STORE: 1) User's question or request, 2) Your
  • Memory Search: Search stored memories for past conversations, user preferences, project context, and decisions. USE THIS TOOL: 1) At start of every conversation to find related context, 2) When user m
  • Memory Get Spaces: List all available memory spaces (project contexts). USE THIS TOOL: To see what spaces exist before searching or storing memories. Each space organizes memories by topic (e.g., 'Pro

What data it sees

Do you need an account

No: the server works without sign-in

Recall past conversations and user preferences with searchable long‑term memory. Organize work into spaces and quickly load rich project context. Act across connected services like GitHub, Linear, and Slack with discoverable integration actions.

How to connect

How to connect core to Claude

The server address to paste into Claude settings:

https://core--harshith.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 core to ChatGPT

The server address to paste into ChatGPT settings:

https://core--harshith.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 core to Cursor

The server address to paste into Cursor settings:

https://core--harshith.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 (9)

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

memory_ingestStore conversation in memory for future reference. USE THIS TOOL: At the END of every conversation after fully answering the user. WHAT TO STORE: 1) User's question or request, 2) Your solution or explanation, 3) Important decisions made, 4) Key insights discovered. HOW TO USE: Put the entire conversation summary in the 'message' field. IMPORTANT: You MUST provide a sessionId - if you don't have one, call initialize_conversation_session tool FIRST to obtain it at the start of the conversation, then use that SAME sessionId for all memory_ingest calls. Optionally add spaceIds array to organize by project. Returns: Success confirmation with storage ID.
memory_searchSearch stored memories for past conversations, user preferences, project context, and decisions. USE THIS TOOL: 1) At start of every conversation to find related context, 2) When user mentions past work or projects, 3) Before answering questions that might have previous context. HOW TO USE: Write a simple query describing what to find (e.g., 'user code preferences', 'authentication bugs', 'API setup steps'). Returns: Markdown-formatted context optimized for LLM consumption, including session compacts, episodes, and key facts with temporal metadata.
memory_get_spacesList all available memory spaces (project contexts). USE THIS TOOL: To see what spaces exist before searching or storing memories. Each space organizes memories by topic (e.g., 'Profile' for user info, 'GitHub' for GitHub work, project names for project-specific context). Returns: Array of spaces with id, name, and description.
memory_about_userGet user's profile information (background, preferences, work, interests). USE THIS TOOL: At the start of conversations to understand who you're helping. This provides context about the user's technical preferences, work style, and personal details. Returns: User profile summary as text.
memory_get_spaceGet detailed information about a specific space including its full summary. USE THIS TOOL: When working on a project to get comprehensive context about that project. The summary contains consolidated knowledge about the space topic. HOW TO USE: Provide either spaceName (like 'core', 'GitHub', 'Profile') OR spaceId (UUID). Returns: Space details with full summary, description, and metadata.
initialize_conversation_sessionInitialize a session for this conversation. MUST be called FIRST at the start of every conversation before any memory_ingest calls. This generates a unique UUID that tracks the entire conversation session. IMPORTANT: One conversation = one session. Call this tool once at the beginning, store the returned sessionId, and use that SAME sessionId for ALL memory_ingest operations throughout this conversation. DO NOT create custom session IDs. Returns: A UUID string to use as sessionId for all subsequent memory operations.
get_integrationsList all connected integrations (GitHub, Linear, Slack, etc.). USE THIS TOOL: Before using integration actions to see what's available. WORKFLOW: 1) Call this to see available integrations, 2) Call get_integration_actions with a slug to see what you can do, 3) Call execute_integration_action to do it. Returns: Array with slug, name, accountId, and hasMcp for each integration.
get_integration_actionsGet list of actions available for a specific integration. USE THIS TOOL: After get_integrations to see what operations you can perform. For example, GitHub integration has actions like 'get_pr', 'get_issues', 'create_issue'. HOW TO USE: Provide the integrationSlug from get_integrations (like 'github', 'linear', 'slack'). Returns: Array of actions with name, description, and inputSchema for each.
execute_integration_actionExecute an action on an integration (fetch GitHub PR, create Linear issue, send Slack message, etc.). USE THIS TOOL: After using get_integration_actions to see available actions. HOW TO USE: 1) Set integrationSlug (like 'github'), 2) Set action name (like 'get_pr'), 3) Set arguments object with required parameters from the action's inputSchema. Returns: Result of the action execution.