Common Room

Track community activity across channels and identify key contributors.

CommunityOnlineNo sign-inGlobalFreeRead-only

What it can do

  • Commonroom Get Catalog: Returns available object types, their properties, allowed sort fields, and association metadata for Common Room API queries. Each object may include an "assocs" array with part
  • Commonroom List Objects: Retrieves Common Room objects (contacts, organizations, segments, etc.) with pagination, filtering, and sorting. Call commonroom_get_catalog first to discover available object
  • Commonroom Submit Feedback: Submit feedback about query results. Use after presenting data to the user. When to use: - User indicates the results were helpful/useful - User says the data was not what

What data it sees

Do you need an account

No: the server works without sign-in

Track community activity across channels and identify key contributors. Monitor engagement signals, manage contacts, and surface product-qualified leads.

How to connect

How to connect Common Room to Claude

The server address to paste into Claude settings:

https://commonroom.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 Common Room to ChatGPT

The server address to paste into ChatGPT settings:

https://commonroom.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 Common Room to Cursor

The server address to paste into Cursor settings:

https://commonroom.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 (3)

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

commonroom_get_catalogReturns available object types, their properties, allowed sort fields, and association metadata for Common Room API queries. Each object may include an "assocs" array with partial metadata about connected objects. Each assoc has "targetEntity" (display name), "targetObjectTypeId" (null for Contact/Organization, "cot_X" for custom objects), and "objectAssocType" (e.g. "default" or a smart account link type).
commonroom_list_objectsRetrieves Common Room objects (contacts, organizations, segments, etc.) with pagination, filtering, and sorting. Call commonroom_get_catalog first to discover available objects, their filter fields, allowed properties, and sort options. Full tool-call examples: 1. Contacts by name in a segment: { "objectType": "Contact", "filter": { "type": "and", "clauses": [{ "type": "stringFilter", "field": "fullName", "params": { "op": "like", "value": "Tracy" } }, { "type": "stringListFilter", "field": "memberSegmentId", "params": { "op": "any", "value": ["s_1"] } }] }, "properties": ["primaryEmail", "title", "companyName"], "limit": 20 } 2. Recent conversation threads sorted by time: { "objectType": "Activity", "filter": { "type": "and", "clauses": [{ "type": "dateRangeFilter", "field": "activityTime", "params": { "op": "in", "value": "P7D", "min": null, "max": null } }, { "type": "booleanFilter", "field": "activityIsParent", "params": { "op": "eq", "value": true } }] }, "properties": ["content", "url"], "sort": "activityTime", "direction": "desc", "limit": 50 } 3. Large organizations sorted by member count: { "objectType": "Organization", "filter": { "type": "and", "clauses": [{ "type": "numberFilter", "field": "groupCompanySize", "params": { "op": "gte", "value": 100 } }] }, "sort": "member_count", "direction": "desc", "limit": 25 } 4. Contacts with email who are engineers or managers (AND+OR): { "objectType": "Contact", "filter": { "type": "and", "clauses": [{ "type": "booleanFilter", "field": "memberHasEmail", "params": { "op": "eq", "value": true } }, { "type": "or", "clauses": [{ "type": "stringFilter", "field": "title", "params": { "op": "like", "value": "Engineer" } }, { "type": "stringFilter", "field": "title", "params": { "op": "like", "value": "Manager" } }] }] }, "properties": ["primaryEmail", "title", "companyName"] } 5. Activities between two dates: { "objectType": "Activity", "filter": { "type": "and", "clauses": [{ "type": "dateRangeFilter", "field": "acti
commonroom_submit_feedbackSubmit feedback about query results. Use after presenting data to the user. When to use: - User indicates the results were helpful/useful - User says the data was not what they were looking for - User provides specific feedback about data quality