Mcp Bruno

🔌 Bruno MCP Server for Python

Python MCP server for running Bruno collections. It exposes a Model Context Protocol server over stdio with tools that run collections through the bru CLI and return normalized JSON results.

Note: All examples in this repository use placeholder names (project1, /home/user/project/bruno, example.test). Replace them with your own paths and collection names.

✨ Features

• Run Bruno collections natively using the Bruno CLI.
• Discover collections and sibling environment files automatically.
• Support environment files and dynamic environment variables.
• Secure Secret Injection: Pass secrets to Bruno without exposing values to the LLM via inherited_variables. Secret values are injected through a temporary, owner-only --env-file and the child process environment — they never appear in CLI arguments (ps output) or logs.
• Filter Inspection: Inspect documented query filters and run temporary filter scenarios without modifying the source collection.
• Two-Phase Full Validation: Execute baseline tests + all documented filters in a single tool call.
• Normalized Outputs: Return structured execution results containing success, summary, failures, and timings.

📦 Requirements

• Python: 3.10 or newer
• Package Manager: uv
• Node Package Manager: npm (only if the Bruno CLI is not already installed)

The installer checks whether the Bruno CLI command bru is available. If it is missing, the server fails with an explicit error instead of silently installing packages. To install the pinned version manually:

npm install -g @usebruno/[email protected]

Runtime auto-install is available but opt-in: set BRUNO_MCP_AUTO_INSTALL_BRU=1 (or auto_install = true under [bruno] in the config file) and the server installs exactly the pinned version from cli_version / BRUNO_MCP_BRU_VERSION.

🚀 Installation & Running

1. Installation

Install dependencies using uv:

uv sync

(If your configured package index does not mirror the MCP Python SDK, point uv at PyPI for the sync: UV_DEFAULT_INDEX=https://pypi.org/simple uv sync)

2. Running the Server

You can run the server directly using uv:

uv run bruno-mcp

Alternatively, run the module directly inside the uv environment: uv run python -m bruno_mcp

⚙️ Configuration

MCP Configuration

Example MCP stdio configuration from this workspace root:

{  "mcpServers": {    "bruno-runner": {      "command": "uv",      "args": ["run", "bruno-mcp"]    }  }}

Configuration File (bruno-mcp.toml)

Default roots and auth aliases can be configured in bruno-mcp.toml in the current working directory, or globally in ~/.config/bruno-mcp/config.toml.

See bruno-mcp.example.toml for a commented template:

[workspace]roots = [  "/home/user/project/bruno"]
[bruno]cli_version = "4.2.0"   # pinned Bruno CLI versionauto_install = false     # never install bru silently at runtime
[limits]run_timeout_seconds = 300max_output_bytes = 8388608max_concurrent_runs = 2
[artifacts]ttl_hours = 24           # raw reports are auto-deleted after thismax_files = 50
[security]enforce_root_confinement = true   # reject collection paths outside workspace roots
[auth]inherited_variables = [  "BRUNO_AUTH_TOKEN",  "BRUNO_API_KEY"]
[defaults]environment = "dev"

Every setting can also be set via environment variables (BRUNO_MCP_BRU_VERSION, BRUNO_MCP_AUTO_INSTALL_BRU, BRUNO_MCP_RUN_TIMEOUT, BRUNO_MCP_MAX_OUTPUT_BYTES, BRUNO_MCP_MAX_CONCURRENT_RUNS, BRUNO_MCP_ARTIFACTS_DIR, BRUNO_MCP_ARTIFACT_TTL_HOURS, BRUNO_MCP_ARTIFACT_MAX_FILES, BRUNO_MCP_ENFORCE_ROOT_CONFINEMENT, BRUNO_MCP_LOG_LEVEL), which take precedence over the file.

Note: The installer creates ~/.config/bruno-mcp/config.toml with a dummy root. Local bruno-mcp.toml files are git-ignored so real paths and environment names are never committed.

💻 Local VS Code Installation

From the project root, install dependencies with uv:

UV_DEFAULT_INDEX=[https://pypi.org/simple](https://pypi.org/simple) uv sync

Ensure the Bruno CLI is available (bru --version). This repository includes .vscode/mcp.json, allowing VS Code to discover the local MCP server from the workspace:

{  "servers": {    "bruno-runner": {      "type": "stdio",      "command": "uv",      "args": ["run", "bruno-mcp"]    }  }}

Reload the VS Code window after syncing dependencies. The bruno-runner server should now be available in the MCP servers list.

Global Installation

To install the MCP server in the VS Code user profile so it is available from any workspace:

uv run python scripts/install_vscode.py

(To also install the reusable Copilot prompt and agent globally, append --with-copilot-customizations to the command above).

To install it manually in another local VS Code workspace, change the command args to include --directory:

"args": ["--directory", "/home/user/mcp-bruno", "run", "bruno-mcp"]

🧰 Available Tools

🔍 list-collections

Lists Bruno collections below a root directory or configured roots. Use it when the user provides a partial collection name instead of a full path.

• root (optional): Bruno root directory (usually contains collections/ and environments/).
• query (optional): Case-insensitive text used to filter collection names and paths.

▶️ run-collection

Runs a Bruno collection and returns normalized execution results.

• collection (required): Path to the Bruno collection.
• environment (optional): Path to an environment file.
• variables (optional): Environment variables as KEY=value strings.
• inherited_variables (optional): Names of environment variables to read from the MCP server process and inject into Bruno without exposing values to the LLM. Values travel via a temporary owner-only --env-file and the child process environment ({{process.env.NAME}} also works) — never in CLI arguments.

{  "collection": "/home/user/project/bruno/collections/project1",  "environment": "dev",  "inherited_variables": ["BRUNO_AUTH_TOKEN"]}

🌍 discover-environments

Inspects the folder structure around a Bruno collection and returns the sibling environments directory, available environment names, and variable names (without returning secret values).

📖 read-result-artifact

Reads a bounded, redacted summary from the raw Bruno JSON artifact path returned by run-collection.

• path (required): The artifact.path value returned by a previous run.
• max_items (optional): Number of response items to sample per request (default 3, max 20).

🧪 list-request-filters & run-filter-scenarios

• list-request-filters: Inspects YAML request files and returns query params split into enabled and disabled groups.
• run-filter-scenarios: Runs temporary request variants with selected disabled query params enabled without modifying the source files.

🛡️ run-full-validation

Two-phase orchestration in a single tool call:

1. Baseline: Runs the collection once and checks every endpoint responds without errors (no 4xx/5xx).
2. Filters: Only runs if the baseline is green. Automatically discovers and tests every disabled query filter across every endpoint.

Agent Skills & Copilot Integration

These workflows use the MCP server configured as bruno-runner; installing a skill or prompt does not install or configure the server. Configure the server in your client first using the MCP configuration above.

VS Code GitHub Copilot

The repository includes a custom agent and a slash-command prompt. From this repository root, copy them into the target workspace:

mkdir -p /path/to/workspace/.github/agents /path/to/workspace/.github/promptscp copilot/agents/bruno-runner.agent.md /path/to/workspace/.github/agents/cp copilot/prompts/run-bruno-collection.prompt.md /path/to/workspace/.github/prompts/

Select the bruno-runner custom agent in Copilot Chat's agent picker (@bruno-runner where supported), or run /run-bruno-collection <collection or path> [environment] in Chat. The slash command works independently of selecting the custom agent.

Alternatively, install both globally with:

uv run python scripts/install_vscode.py --with-copilot-customizations

Claude Code / Cursor / Windsurf

The universal Bruno Runner skill consolidates collection discovery, environment selection, standard runs, targeted filter scenarios, full two-phase validation, secret safety, and reporting rules.

For Claude Code, copy it into the target project's skill directory:

mkdir -p /path/to/workspace/.claude/skills/bruno-runnercp skills/bruno-runner/SKILL.md /path/to/workspace/.claude/skills/bruno-runner/SKILL.md

Or symlink the skill directory using an absolute source path:

mkdir -p /path/to/workspace/.claude/skillsln -s /absolute/path/to/mcp-bruno/skills/bruno-runner /path/to/workspace/.claude/skills/bruno-runner

For Cursor, copy or symlink the same directory to .cursor/skills/bruno-runner/; for Windsurf, use .windsurf/skills/bruno-runner/ in the target workspace. Skill discovery depends on your client's version and configuration. For clients using rules instead, adapt the skill body into their native rule format (for example, a .cursor/rules/bruno-runner.mdc file with Cursor rule frontmatter); merely copying SKILL.md into a rules directory does not guarantee activation.

Ask to run a collection, validate a specific filter, or test all endpoints and filters. The workflows resolve secrets locally through inherited_variables; never paste credentials into chat. The server's local token fallback is ~/.config/bruno-mcp/.bearer_token (raw token), not ~/.config/mcp-bruno/.bearer_token. After updating it, restart the MCP server.

Repository Assets

Skills and Copilot templates remain organized under skills/ and copilot/ at the repository root, separately from the Python packages discovered under src/ in pyproject.toml. They are repository assets, not installed wheel resources; use a repository checkout for the copy, symlink, and installer commands above. Installing the Python package alone does not register agent workflows with a client.

Execution results retain the server's normalized output contract:

{  "success": true,  "summary": {    "total": 5,    "failed": 0,    "passed": 5  },  "failures": [],  "auth_failure": false,  "auth_message": null,  "timings": {    "started": "2024-03-14T10:00:00.000000Z",    "completed": "2024-03-14T10:00:01.000000Z",    "duration": 1000  }}

🐳 Docker

The Docker image installs both this Python server and the Bruno CLI:

docker build -t bruno-mcp-python .docker run --rm -i bruno-mcp-python

🛠️ Development & Project Structure

Commands:

• Compile-check the sources: uv run python -m compileall src
• Run the test suite: uv run python -m unittest discover -s tests -v

Structure:

.├── src/bruno_mcp/         # MCP server, runner, config, and types├── scripts/               # VS Code installer script├── copilot/               # Reusable Copilot prompt and agent templates├── skills/bruno-runner/    # Universal Agent Skill (SKILL.md)├── tests/                 # Unit tests├── .vscode/mcp.json       # Workspace MCP server entry└── bruno-mcp.example.toml # Commented configuration template

mcp-name: io.github.kta41/mcp-bruno

📄 License

Released under the MIT License.