Zed Agent MCP

Zed’s Agent Panel can call Bifrost through Model Context Protocol. This is separate from Zed editor/LSP support: configure MCP when you want the agent to call analyzer-backed tools such as get_summaries.

Until Bifrost is published through the official MCP registry, configure Bifrost as a custom stdio context server in settings.json.

Configure MCP

Build or install Bifrost first. To install the release verified with this setup explicitly:

cargo install brokk-bifrost --version 0.8.9 --locked --force
bifrost --version

The version check should print bifrost 0.8.9.

For local development, build this checkout and use an absolute path to the debug binary:

cargo build --bin bifrost

Add a context_servers entry to your Zed settings:

{
  "context_servers": {
    "bifrost": {
      "command": "/path/to/bifrost",
      "args": ["--root", "/path/to/project", "--mcp", "symbol|extended"],
      "env": {}
    }
  }
}

For a local checkout build, command should point at /path/to/bifrost/target/debug/bifrost. Always pass an explicit --root; otherwise Bifrost analyzes whatever directory Zed uses as the subprocess working directory.

symbol|extended exposes the analyzer-backed code-intelligence tools used by the Bifrost agent package, including search_symbols, get_summaries, scan_usages_by_location, get_symbol_locations, and related repository discovery tools. Use a smaller or larger MCP toolset only when the host should see a different surface. See MCP Server for the available toolsets.

Open Settings → AI → MCP Servers and confirm that Bifrost’s indicator is green and its tooltip says Server is active. If the server is disabled, enable it there.

Enable Bifrost in an Agent Profile

An active MCP server is not automatically callable from every Zed Agent profile. The profile selected for a thread controls which MCP tools that thread can use. A server can therefore be running correctly while the agent reports that search_symbols or query_code is unavailable.

Run agent: manage profiles from the command palette, create or configure a profile, and enable the Bifrost tools you want under its MCP tools. For a focused code-intelligence profile, the corresponding settings.json shape is:

{
  "agent": {
    "profiles": {
      "bifrost": {
        "name": "Bifrost",
        "enable_all_context_servers": false,
        "context_servers": {
          "bifrost": {
            "tools": {
              "search_symbols": true,
              "get_summaries": true,
              "query_code": true
            }
          }
        }
      }
    }
  }
}

The profile’s bifrost key must match the name used under the top-level context_servers configuration. Start a new Zed Agent thread and select this profile. Existing threads retain the tool surface with which they were created.

Zed asks for confirmation before MCP calls by default. Approve the first Bifrost call when prompted, or configure Zed’s tool permissions if you want a different approval policy.

Validate the Setup

Use a prompt that requires a Bifrost MCP tool result instead of ordinary file reading:

Use the Bifrost MCP get_summaries tool on src/main.rs. Reply with the symbols returned by the tool.

A successful response should name analyzer symbols from the MCP result, such as modules, classes, fields, or functions from the target file. If the agent says it cannot access Bifrost tools and falls back to reading files directly, check that:

• the context_servers entry is present in the active Zed settings file,
• the server is active under Settings → AI → MCP Servers,
• the selected Agent profile enables the requested Bifrost tool,
• the command path points at an existing Bifrost binary,
• --root points at the project you want analyzed, and
• the thread was created after the server and profile were configured.

Avoid prompts that only ask about README.md or docs files; those can pass through ordinary file reading without proving the MCP server ran.

Apply the shared host-integration evidence contract: retain Zed’s Bifrost tool event and structured result for a known workspace declaration, verify its project-relative source path, and reject paths under the configured binary’s install directory or another repository.

Can My Agent Run RQL?

The configuration above uses symbol|extended. In a new Agent thread, confirm that the Bifrost tool list includes query_code, then call it with the inline JSON fields {"match":{"kind":"declaration"},"limit":1}. To validate saved RQL, check a workspace file named bifrost-smoke.rql containing (limit 1 (declaration)), then call query_code with {"query_file":"bifrost-smoke.rql"}.

The inline call is canonical JSON. MCP accepts RQL only from a workspace .rql file through query_file. See MCP query and RQL availability for the full surface matrix and Agent Result Safety before making completeness claims.