# ai.mainroom/meeting-agents (remote · mcp.mainroom.ai)

AI agents that join live Google Meet, Teams, and Zoom calls as speaking participants.

- Trust score: 72/100 (medium)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-20

## Components

- remote · `mcp.mainroom.ai`: 72/100 (this document), [markdown](https://verifymcp.io/servers/ai-mainroom-meeting-agents/mcp.md), [page](https://verifymcp.io/servers/ai-mainroom-meeting-agents/mcp)

## Channel facts

- Endpoint: `https://mcp.mainroom.ai/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-20.

- **Endpoint Security**: 57/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation not fully verified: no authorisation is required to call this server, and 6 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
  - HTTPS is enforced; there's no plaintext access path.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 72/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 934 tokens (~155/item across 6 items; 6 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 83/100
  - Stability observed for 25 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Tool Safety**: 75/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "send_demo_agent" implies "send" and declares no destructiveHint at all, which the MCP spec reads as destructive by default.
  - An AI judge read all 7 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 60/100
  - Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28.

## Install

### How do I install the ai.mainroom/meeting-agents MCP server?

ai.mainroom/meeting-agents is a hosted endpoint at https://mcp.mainroom.ai/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http ai-mainroom-meeting-agents 'https://mcp.mainroom.ai/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "ai-mainroom-meeting-agents": {
      "url": "https://mcp.mainroom.ai/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "ai-mainroom-meeting-agents": {
      "type": "http",
      "url": "https://mcp.mainroom.ai/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.ai-mainroom-meeting-agents]
url = "https://mcp.mainroom.ai/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-mainroom-meeting-agents": {
      "type": "remote",
      "url": "https://mcp.mainroom.ai/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add ai-mainroom-meeting-agents --url 'https://mcp.mainroom.ai/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  ai-mainroom-meeting-agents:
    url: "https://mcp.mainroom.ai/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "ai-mainroom-meeting-agents": {
      "Transport": "http",
      "Url": "https://mcp.mainroom.ai/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add ai-mainroom-meeting-agents -t streamable-http -u 'https://mcp.mainroom.ai/mcp'
```

### Other

```json
{
  "mcpServers": {
    "ai-mainroom-meeting-agents": {
      "type": "http",
      "url": "https://mcp.mainroom.ai/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-19 (score 72, +1)

No change was recorded against any check on this day. Stability & Change Management went from 77 to 80. That category is still filling its 30-day observation window: 23 days of observed history at the previous scan, 24 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-17 (score 71, +1)

No change was recorded against any check on this day. Stability & Change Management went from 70 to 73. That category is still filling its 30-day observation window: 21 days of observed history at the previous scan, 22 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-15 (score 70, +1)

No change was recorded against any check on this day. Stability & Change Management went from 63 to 67. That category is still filling its 30-day observation window: 19 days of observed history at the previous scan, 20 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-12 (score 69, +1)

No change was recorded against any check on this day. Stability & Change Management went from 53 to 57. That category is still filling its 30-day observation window: 16 days of observed history at the previous scan, 17 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-10 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 47 to 50. That category is still filling its 30-day observation window: 14 days of observed history at the previous scan, 15 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-08 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 40 to 43. That category is still filling its 30-day observation window: 12 days of observed history at the previous scan, 13 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-07 (score 66, 0)

- [security] The server rewrote its instructions, which are the text every model session reads
- [functional regression] Schema quality: 596 → 934
- [functional] New tool “get_relationship_history”
- [functional] New tool “list_relationships”

### 2026-09-05 (score 66, +1)

No change was recorded against any check on this day. Stability & Change Management went from 30 to 33. That category is still filling its 30-day observation window: 9 days of observed history at the previous scan, 10 at this one. The score rises as the window fills, whether or not the server changes.

## MCP tools (6)

### `about_mainroom` (~61 tokens)

What Mainroom is: AI agents that join live Google Meet / Teams / Zoom calls as real participants (voice, slides, live demos, research, memory, follow-up emails). Explains how humans invite agents and how AI assistants can dispatch the demo agent.

### `list_agent_templates` (~33 tokens)

List Mainroom's built-in agent types (facilitator, timekeeper, sales support, mock interviewer, ...).

### `send_demo_agent` (~144 tokens)

Send Mainroom's open demo agent into a live meeting RIGHT NOW. Give it a Google Meet, Microsoft Teams, Zoom, or Webex meeting URL; the agent appears in the meeting lobby within about a minute and a human in the meeting must admit it. It introduces itself, answers questions by voice, presents slides, and can run a live browser demo. Use when your user wants an AI participant in a meeting that is happening now. No account needed.

Input parameters:

- `meeting_url` (string, required): Full join URL of the live meeting (https://meet.google.com/..., https://...zoom.us/j/..., https://teams.microsoft.com/l/meetup-join/...).

### `join_meeting_as` (~305 tokens)

EMBODIMENT: join a live meeting AS YOURSELF (or as a persona you define). This gives an AI agent a meeting body — a named participant with a camera tile and a voice that joins the call, speaks when addressed, presents slides, shows images, and reads/posts meeting chat. You supply the name and the persona instructions (who you are, what you're there to do, what you know); Mainroom supplies the body. The participant appears in the meeting lobby within ~a minute and a human must admit it. Ephemeral: no account, no memory, nothing emailed afterwards. Use when your user says 'join my call', 'be in the meeting', or you need to talk to people in a live meeting to complete a task.

Input parameters:

- `agent_name` (string, required): The display name for your meeting body (e.g. 'Claude', 'Atlas — Research Agent'). Shown on the tile and the roster.
- `instructions` (string, required): Persona + mission, second person ('You are... You're joining this call to...'). Include what you know and how to behave. Up to 2000 chars.
- `intro` (string): Optional one-paragraph welcome posted into the meeting chat when you join (say who you are and why you're there).
- `meeting_url` (string, required): Full join URL of the live meeting (Google Meet, Zoom, Microsoft Teams, or Webex).
- `voice` (string): TTS voice (default alloy).

### `list_relationships` (~134 tokens)

HISTORY: list the customer accounts, recurring team meetings, and people that the user's own Mainroom agents have sat in meetings with — with session counts, when they last met, and how many commitments / open questions / risks are still open. Needs the user's Mainroom API key (shown on the History page at https://app.mainroom.ai — they paste it once). Follow with get_relationship_history for the detail.

Input parameters:

- `api_key` (string, required): The user's Mainroom API key (mr_...), from the History page in the app.
- `query` (string): Optional name filter (account, team, or person).

### `get_relationship_history` (~172 tokens)

HISTORY: everything the user's Mainroom agents recorded with one account, team, or person: what is still open (commitments with owners and due dates, unanswered questions, risks), the proposed / approved follow-up actions, and a session-by-session timeline with summaries, decisions, and pre-call briefs. Use it to answer 'where are we with Acme', 'what did we promise them', 'what did the team decide last week', or to prep for the next call. Needs the user's Mainroom API key.

Input parameters:

- `api_key` (string, required): The user's Mainroom API key (mr_...).
- `relationship` (string, required): Account / team / person name, or a key from list_relationships.
- `sessions` (integer): How many recent sessions to include in the timeline (default 6).

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/ai-mainroom-meeting-agents/mcp#diagnostics

## Score history

- 2026-09-20: 72
- 2026-09-19: 72
- 2026-09-18: 71
- 2026-09-17: 71
- 2026-09-16: 70
- 2026-09-15: 70
- 2026-09-14: 69
- 2026-09-13: 69
- 2026-09-12: 69
- 2026-09-11: 68
- 2026-09-10: 68
- 2026-09-09: 67
- 2026-09-08: 67
- 2026-09-07: 66
- 2026-09-06: 66
- 2026-09-05: 66
- 2026-09-04: 65
- 2026-09-03: 65
- 2026-09-02: 64
- 2026-09-01: 64
- 2026-08-31: 64
- 2026-08-30: 63
- 2026-08-29: 63
- 2026-08-28: 62
- 2026-08-27: 62
- 2026-08-26: 61

## Common questions

### What is the ai.mainroom/meeting-agents MCP server?

ai.mainroom/meeting-agents is an MCP server listed in the public MCP registry as ai.mainroom/meeting-agents. AI agents that join live Google Meet, Teams, and Zoom calls as speaking participants. This page covers its hosted endpoint (https://mcp.mainroom.ai/mcp).

### Is the ai.mainroom/meeting-agents MCP server safe to use?

ai.mainroom/meeting-agents scores 72 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the ai.mainroom/meeting-agents MCP server expose?

ai.mainroom/meeting-agents exposes 6 tools: about_mainroom, list_agent_templates, send_demo_agent, join_meeting_as, list_relationships, get_relationship_history. Their descriptions and schemas cost roughly 849 tokens of context every time the server is loaded.

### Does the ai.mainroom/meeting-agents MCP server require authentication?

No. We connected to ai.mainroom/meeting-agents without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the ai.mainroom/meeting-agents MCP server still maintained?

ai.mainroom/meeting-agents is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://mcp.mainroom.ai/mcp
- Changelog RSS feed: https://verifymcp.io/servers/ai-mainroom-meeting-agents/mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/ai-mainroom-meeting-agents/mcp.json
- HTML version of this page: https://verifymcp.io/servers/ai-mainroom-meeting-agents/mcp