MCP servers for Claude Code and every agent: set up and inspect them per repo

What is MCP?

MCP (Model Context Protocol) is an open protocol, introduced by Anthropic, that lets AI agents call external tools and data sources through one standard interface. Each integration runs as an MCP server: a small program or remote endpoint that exposes tools such as querying a database, reading an issue tracker or searching internal docs. An agent that supports MCP connects to the servers listed in its config and calls their tools during a task.

Two transports cover most setups. With stdio, the agent starts the server as a local process and talks to it over standard input and output. With HTTP, the server runs somewhere else and the agent connects to a URL. The glossary has short definitions of the related terms.

How do coding agents like Claude Code use MCP servers?

Each agent reads MCP servers from its own config files and starts or connects to them itself. A project-level file, most commonly .mcp.json at the repository root, gives everyone who clones the repo the same servers. Agents can also keep personal servers in user-level settings outside the repo.

Tallos does not ship its own MCP servers and does not change how agents load them. When you start Claude Code or another MCP-capable agent in a Tallos workspace, it reads its configs exactly as it would in any terminal. What Tallos adds is visibility: for each repository, you can see which servers your agents will find before you start them.

Every Tallos workspace is a git worktree of the same repo, so a committed .mcp.json exists in all of them and parallel workspaces get the same servers. An uncommitted file exists only in the workspace where you created it.

What does the MCP Configs inspector in Tallos show?

MCP Configs is a section in Settings → Projects → *your repo* that inspects the MCP server definitions agents can use in that repository. It reads the root of the repo's active workspace (or its main worktree when no workspace of that repo is active), checks four known config files and lists every server under their mcpServers object.

• Per file: a status of not found, invalid JSON, unreadable, no servers, or the server count, plus Open to edit the file in the Tallos editor.
• Per server: name, transport (stdio or http), the command or URL, the env block, and a status of enabled, disabled or invalid.
• Invalid servers say why, for example *Missing command or URL* or *Missing URL*.
• Checked files that don't exist are listed under *Checked*, so you know exactly what was looked for.

The inspector understands the common dialects: command as a string or an array, url or httpUrl, and type values such as http, remote and local. A server marked "disabled": true or "enabled": false shows as disabled. Files over 256 KB, or with more than 256 servers, are reported as invalid instead of being parsed.

How do I set up an MCP server for Claude Code in my repo?

Add the server to a .mcp.json file at the repository root, check it in MCP Configs, commit it, and start your agent in a workspace. The example uses the standard mcpServers format.

1. 1

   Open MCP Configs

   In Tallos, go to Settings → Projects, pick the repository and scroll to MCP Configs. Searching settings for mcp or .mcp.json jumps there too.

2. 2

   Create the file

   If the repo has no MCP config, click Add MCP config, then Create empty config to confirm. Tallos writes .mcp.json with an empty mcpServers object and opens it in the editor.

3. 3

   Add your servers

   Add one entry per server under mcpServers. Local servers use command, args and optional env. Remote servers use "type": "http" and a url.

4. 4

   Refresh and check

   Click refresh in MCP Configs. Each server should show the right transport and enabled. Fix anything marked invalid before you start an agent.

5. 5

   Commit and run

   Commit .mcp.json so every workspace and teammate gets it, then start Claude Code or another MCP-capable agent in a workspace. The agent loads the servers itself.

{
  "mcpServers": {
    "internal-docs": {
      "command": "node",
      "args": ["./tools/mcp/docs-server.js"],
      "env": {
        "DOCS_DIR": "./docs"
      }
    },
    "issue-tracker": {
      "type": "http",
      "url": "https://mcp.example.com/mcp"
    }
  }
}

In MCP Configs, internal-docs appears as stdio with the command node, and issue-tracker as http with its URL. Both show enabled.

See what your agents will load

Install Tallos, add your repo and check its MCP Configs before you start your agents.

Get Tallos →

How do I keep MCP secrets out of git?

Keep API keys and tokens out of any MCP config you commit. A committed .mcp.json is readable by everyone with access to the repo and by every agent working in it.

• Don't commit literal secrets. Put servers that need personal tokens in your agent's user-level config, outside the repo, or use environment-variable references if your agent supports them. Check its docs for the syntax.
• Masking is for the screen, not the file. Tallos masks an env value when its key looks sensitive (token, secret, password, api_key, auth, bearer, cookie, session, credential, private_key) or when the value looks like a known token format such as sk-… or ghp_…. It shows ••••••••; the file on disk is unchanged.
• Ignore personal files. If you keep a personal MCP file inside the repo folder, add it to .gitignore.
• Read before you run. A stdio server is a program the agent starts on your machine. Check the commands in MCP Configs before you open an agent in a repo you just cloned.

Does MCP Configs work with SSH repos?

Yes. For a repository on a remote workspace, Tallos reads the config files through the remote filesystem over SSH. The repo has to be connected; if it isn't, MCP Configs asks you to connect it first. Creating a starter config on a remote repo is limited to the workspace root .mcp.json.

MCP Configs appears for git repositories. Plain folder projects don't have the section.

How do MCP servers relate to the tallos CLI and skills?

They solve different problems and work side by side. MCP servers give an agent tools from outside systems. The tallos CLI and bundled skills let the agent drive Tallos itself: create workspaces, read terminals, use the built-in browser. Agent skills are the instructions that tell an agent when to use which.