> ## Documentation Index > Fetch the complete documentation index at: https://test-8ad8522e-docs-compliance-guide-refine.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # MCP (External Tool Connections) > Use the Model Context Protocol (MCP) to connect AI SRE agents to external tools and data sources — such as GitHub, Slack, Kubernetes, and observability platforms. Configure MCP servers, authentication, and scope in the console; agents will call their tools on demand during a session. **Private beta**: AI SRE is currently in private beta and available to invited accounts only. To join the whitelist test, contact the Flashduty sales team to request access; features and the UI may change during the beta. ## Overview *** **MCP** (Model Context Protocol) lets AI SRE agents connect to external tools and data sources. Each **MCP server** is a standardized endpoint that exposes a set of tools (functions) — for example, querying GitHub issues, sending Slack messages, reading Kubernetes resources, or retrieving metrics from an observability platform. Once you configure and enable an MCP server in the console, agents will **autonomously decide** when they need an external capability during incident investigation and call the corresponding tool directly — no manual data-shuttling required. This page covers the **"MCP" section inside the AI SRE console** — that is, **third-party MCP servers that agents call** (you bring external tools in for agents to use). This is **different** from the [Flashduty MCP Server](/en/developer/mcp-server) in the developer docs: that is **Flashduty's own outbound MCP service**, which lets you connect **Flashduty's capabilities into third-party AI clients** (such as Claude or Cursor). One direction is "agents calling external services"; the other is "external clients calling Flashduty" — they are opposite flows, not the same thing. ## What Is MCP *** **MCP** (Model Context Protocol) is an open protocol that describes in a uniform way "what tools a server exposes, what parameters each tool accepts, and what it returns." Think of it as the "USB port" of the AI agent world — any MCP-compliant server can be discovered and called plug-and-play by an agent, with no per-system adapter code required. In AI SRE, MCP extends an agent's capability from "built-in tools" to "any external system": * You add an MCP server in the console (declaring its endpoint, transport, and authentication). * At session start, enabled servers visible in the current scope become available to the agent. * When needed, the agent discovers the tools that server provides and calls them directly. **MCP vs. Skills**: MCP provides **the ability to connect external tools**; a Skill provides **the methodology for orchestrating those tools to accomplish a class of tasks**. A Skill can declare which MCP server tool it needs inside `SKILL.md` using `mcp:server/tool` notation. See [Skills](/en/ai-sre/skills) for details. ## Adding an MCP Server *** Go to **Plugins → MCP**, click **Add Server** in the top-right corner, and fill in the form to define an MCP server. ### Basic Fields | Field | Type | Required | Description | | ----------- | -------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Name | string | Yes | The server name, used as the identifier when agents call it (e.g., `sqlite-explorer` in `mcp:sqlite-explorer/query`). Must start with a letter; may only contain letters, digits, `-`, and `_`; length 1–255. **Case-insensitive and unique** within an account; cannot duplicate a built-in server name. | | Transport | enum | Yes | How the agent communicates with the server. See "Transport" below. | | Scope | Account / Team | Yes | The scope of this MCP server: **Account** (visible account-wide) or a specific **Team** (visible only to members of that team). See "Scope" below. | | Description | string | Yes | Describes what this server does, for identification in the list. | Each MCP server also has an **AI description**: after an agent first lists a server's tools, the system automatically generates a capability summary from the tool list and displays it in the console. This summary refreshes automatically as the tool set changes — no manual maintenance needed. ### Transport | Transport | Use Case | Required Fields | | ---------------------------- | ------------------------------------------------------------------------------ | --------------------------------------------------------------- | | HTTP Streaming (recommended) | Remote MCP server accessed via an HTTP endpoint | URL (endpoint), optional Headers (JSON) | | SSE (standalone, legacy) | Legacy remote servers that only support Server-Sent Events | URL (endpoint), optional Headers (JSON) | | stdio (local command) | MCP server launched as a local subprocess on the machine where the Runner runs | Command, arguments (one per line), environment variables (JSON) | **stdio is only available for BYOC environments** (Runner deployed on your own machine). Cloud Sandboxes cannot launch local subprocesses. If you are using a cloud environment, use **HTTP Streaming** or **SSE** instead, and ensure the MCP server is reachable from the Sandbox network. For differences between environments, see [Environments (BYOC)](/en/ai-sre/environments). There is a default timeout for both connection and tool calls: 10 seconds for connection, 60 seconds for tool invocation. ### Authentication MCP servers support three **authentication modes** that determine how credentials are provided to the server: All users share the same credentials. Credentials are written directly into the server configuration — for HTTP/SSE transport, in the **Headers** (JSON) (e.g., `{ "Authorization": "Bearer xxx" }`); for stdio transport, in the **environment variables** (JSON) (e.g., `{ "API_KEY": "xxx" }`). Suitable for internal systems accessed with account-level service tokens. Each user provides their own key the **first time** they invoke a tool on this server. Keys are encrypted and stored at the account level, isolated per user. Selecting this mode requires filling in a **Key Schema**: | Field | Required | Description | | ----------- | -------- | ----------------------------------------------------------------------------------------- | | Header Name | Yes | The HTTP header into which the credential is injected in MCP requests (e.g., `X-Api-Key`) | | Placeholder | No | Placeholder hint for the input field (e.g., `sk-...`) | | Help Link | No | Link to documentation explaining how to obtain the key | Suitable for third-party SaaS where each engineer uses their own API key (e.g., a personal GitHub token). Each user authorizes individually via **OAuth 2.1**. An authorization window pops up automatically the first time a tool on this server is invoked. Server discovery and Dynamic Client Registration (DCR) are performed as needed; tokens are stored per user and refreshed automatically near expiry. Suitable for services that support OAuth. For "Per-User API Key" and "Per-User OAuth", if credentials are missing the agent's tool call is paused and a credential entry or authorization dialog is shown to the current user; execution resumes once credentials are supplied. In Shared mode, no credentials are requested from the user. ## Management & Inspection *** The MCP list displays each server's **name** (including its AI description; built-in servers are labeled with a "Built-in" badge), **scope** (account or team name), **transport**, an **enabled** toggle, and an **actions** column. The scope filter bar at the top lets you switch between All / Account / Team views. Toggle the switch in the list. Only **enabled** servers are available to the agent; disabled servers are invisible to agents and cannot be called. Built-in servers are **always enabled** and their toggles cannot be changed. Click the edit button (or click the row) to open the form. You can modify the name, transport, description, endpoint/command, authentication mode, and scope. If you do not have edit permission, the form opens in **read-only** mode with an explanation; built-in servers are likewise read-only. Removes the MCP server from the current scope. **Agents that depend on it will no longer be able to access its tools**, and active sessions currently using it will fail. A confirmation prompt is shown before deletion. ### Inspection: Viewing the Tools a Server Exposes The tools an MCP server exposes are discovered **during a session** by agents on demand — not displayed statically in the console. This is because the same MCP server may have different reachability and tool sets across different environments (Runners); connection state and tool count are per-environment properties, not global ones. To confirm which tools a given MCP server actually exposes in a particular environment, the most direct way is to ask the agent in **Chat** to list that server's tools — it will show the tools and how to use each one. See [Conversations](/en/ai-sre/sessions). Every account comes pre-configured with a **built-in Flashduty MCP server** (labeled "Built-in" in the list, read-only, always enabled), which lets agents read Flashduty incidents, alerts, and other data directly. It is maintained by the platform and requires no configuration on your part. ## Scope *** MCP shares the same **two-level scope** model as other resources (Skills, Knowledge Packs, Agents, Environments), divided into account level and team level: | Scope | Visibility | | ------------- | ------------------------------------- | | Account-level | Visible to all members of the account | | Team-level | Visible only to members of that team | **Edit permissions**: Account owners or account admins can edit any MCP server; team members can edit team-level MCP servers that belong to **their team**. There is no creator-retains-rights exception. When you lack edit permission, the toggle and action buttons for that row appear as **read-only**. **Runtime visibility**: At session start, the agent is offered only **account-level** MCP servers and servers belonging to the **team bound to the current session**. Once the agent reads a team's knowledge during an investigation, that team's MCP servers and Skills are mounted into the session on demand. **The account is the only security boundary at runtime; the team is an ownership and editing tag only.** ## Related Pages *** Skills call MCP-provided tools inside SKILL.md using the `mcp:server/tool` notation. Agents share the same authentication modes and scope model as MCP. stdio MCP servers must run on a BYOC Runner; learn the difference between cloud Sandbox and self-hosted environments. Observe how agents inspect and invoke MCP tools during a session. The opposite direction: the official MCP service for connecting Flashduty into third-party AI clients.