MCP Modal Server

An MCP server for managing Modal — apps, containers, volumes, and secrets — and for deploying & running Modal apps directly from Claude Code and other MCP clients.

Every tool shells out to your local `modal` CLI, so it operates against whatever Modal profile and credentials are configured on your machine. There are no extra tokens to manage.

Installation

The server is published on PyPI as `mcp-modal`. No manual install is needed — the recommended way to run it is with `uvx`, which fetches and launches it on demand. Just point your MCP client at the command below (see Configuration).

Logging in to Modal

This server uses your local Modal credentials. If you haven't authenticated yet, run:

modal setup

This opens a browser to log in and stores a token in `~/.modal.toml`. Already logged in elsewhere? Check with `modal profile current`.

Configuration

Add the server to Claude Code with the `claude mcp` CLI:

claude mcp add mcp-modal -- uvx mcp-modal@latest

Or add it to a `.mcp.json` file in your project root, which is the better option for a team

— everyone who opens the repo gets the same configuration:

{
  "mcpServers": {
    "mcp-modal": {
      "command": "uvx",
      "args": ["mcp-modal@latest"]
    }
  }
}

Why `@latest`, and when to pin instead

`uvx` caches the environment it builds on the first run and does not check PyPI again:

> "uvx will use the latest available version of the requested tool on the first invocation.

> After that, uvx will use the cached version of the tool unless a different version is

> requested, the cache is pruned, or the cache is refreshed."

> — uv docs

So a plain `uvx mcp-modal` means *latest at install time, frozen forever after* — restarting

the client or rebooting changes nothing, because the cache lives on disk. Different people

end up on different versions depending on when they first ran it, with no warning.

• `mcp-modal@latest` re-resolves on every launch, so a restart picks up new releases.

Costs one network round-trip at startup. Use it while the tool surface is still moving.

• `mcp-modal@0.3.0` (an explicit version) is reproducible and upgrades become a

deliberate one-line change. Use it once you want stability, or for a wider audience.

To move a machine that is already stuck on an old cached build, switching it to either form

above is enough — requesting a version invalidates the cache. Otherwise

`uv cache clean mcp-modal` forces a refresh.

Requirements

• Python 3.11 or higher
• `uv` (provides `uvx`)
• Modal CLI 1.5 or newer, configured with valid credentials (`modal setup`) — 1.5 is

where `modal billing summary`/`rates` landed and where the billing report switched to

snake_case columns; the cost tool reads both spellings but needs 1.5 for those two views

• For Modal deploy and run support:
  • The project being deployed/run must use `uv` for dependency management
  • `modal` must be installed in that project's virtual environment

Security

This server shells out to your local `modal` CLI using whatever credentials are in

`~/.modal.toml`. A few tools are powerful by design — if the MCP client driving the server

is ever prompt-injected (for example by malicious text inside logs it fetched), these are

the escalation paths and should stay behind your client's tool-approval prompts rather

than being auto-approved:

• `deploy_modal_app` / `run_modal_app` — execute arbitrary local Python on the host

(`modal deploy` imports the app file; `uv run` resolves and installs the target project's

dependencies).

• `modal_volume_files` with `action="put"` — can read any local file (e.g. `~/.ssh/id_rsa`,

`~/.modal.toml`) and upload it to a cloud volume (a data-exfiltration primitive).

• `modal_volume_files` with `action="get"` and `force=True` — can overwrite any local path

(e.g. `~/.zshrc` or a shell profile, a persistence primitive).

• `manage_modal_container` with `action="exec"` — runs arbitrary commands inside a

container, by design.

Every tool declares MCP tool annotations,

so a client can distinguish the three read-only tools (`list_modal_resources`,

`get_modal_logs`, `search_modal_logs`, all `readOnlyHint: true`) from the seven that change

remote state (`destructiveHint: true`, except `run_modal_app`). Auto-approve the reads;

keep the writes behind a prompt.

Optional local-path allowlist

To contain the two filesystem-touching volume tools, set the

`MCP_MODAL_ALLOWED_LOCAL_PATHS` environment variable to an

`os.pathsep`-separated list of

directories (`:` on macOS/Linux). When it is set, `modal_volume_files` is refused for any

local path — `local_path` on `action="put"`, the destination on `action="get"` — unless the

resolved path, after expanding `~` and collapsing `..`/symlinks, falls inside one of those

roots. The download target `"-"` (return contents instead of writing a file) is exempt

because nothing is written to disk.

When the variable is unset (the default) there is no restriction, so existing setups are

unaffected. Configure it in your MCP client, e.g.:

{
  "mcpServers": {
    "mcp-modal": {
      "command": "uvx",
      "args": ["mcp-modal"],
      "env": { "MCP_MODAL_ALLOWED_LOCAL_PATHS": "/Users/me/modal-workspace:/tmp/modal" }
    }
  }
}

All tools also pass user-supplied names/paths after a `--` end-of-options separator, so a

value beginning with `-` is always treated as data, never as a `modal` CLI flag. Secret

values handed to `manage_modal_secret` are redacted from the echoed command, logs, and any

error output.

Supported Tools

12 tools. Related operations are grouped behind an `action`/`resource` argument rather than

split one-per-CLI-subcommand: every tool schema is loaded into the model's context for the

whole session, so a smaller surface leaves more room for your actual work (and gives the

model fewer near-identical tools to choose between).

Tools that talk to environment-scoped resources take an optional `env` argument to target a

specific Modal environment; if omitted, they

use the profile's default (or `MODAL_ENVIRONMENT`). The exception is `manage_modal_container`

and container logs — a container ID is globally unique and the CLI accepts no environment

there.

Read-only

1. List Modal Resources (`list_modal_resources`) — one lookup for the whole account.

nothing, so an empty directory is distinguishable from a wrong path.

2. Get Modal Logs (`get_modal_logs`) — fetch or stream logs for an app *or* a container.

`auto` — anything starting `ta-` is a container), `timeout_seconds` (default 30),

`env`, `since`, `until`, `tail`, `source` (`stdout`/`stderr`/`system`), `timestamps`,

`follow`

reached, returning a snapshot with `truncated: true`.

"... exited with ...") are Modal dashboard events, not log lines, and won't appear here.

3. Search Modal Logs (`search_modal_logs`) — grep logs and get each hit **with the

surrounding lines**, built for "where did it go wrong?" debugging. Logs are fetched once

and searched locally, so you get context, regex, case control, and exact match counts.

`regex`, `case_sensitive`, `context_lines` (default 3), `max_matches` (default 50),

`since`, `tail` (defaults to the last 1000 entries), `source`,

`exclude` (drop noise lines before searching, e.g. `"queue put failed"`),

`timestamps` (default `true`), `timeout_seconds`, `env`

matched lines are prefixed with `>`, e.g. `> 8: 2026-06-04T... ValueError: bad input`.

The whole fetched log is always searched, so `match_count` stays exact even when fewer

blocks are returned. Reports `excluded_lines` when `exclude` is used.

Deploy & run

4. Deploy Modal App (`deploy_modal_app`)

the output are live and shareable (returned in `urls`).

`strategy` (`rolling`/`recreate`), `stream_logs`

5. Run Modal App (`run_modal_app`)

`timeout_seconds` (default 120)

Pass `detach=True` to keep long jobs alive on Modal past the timeout.

> Why no `modal serve` tool? `modal serve` only keeps its endpoints alive while the

> blocking process runs — an MCP tool that returns would tear them down immediately,

> handing back a dead URL. Use `deploy_modal_app` for a persistent, shareable endpoint.

State changes

6. Manage Modal App (`manage_modal_app`) — `action` is `stop` (shut the app down and

terminate its containers) or `rollback` (redeploy a previous version).

only — defaults to the immediately preceding version), `env`

7. Manage Modal Container (`manage_modal_container`) — `action` is `exec` (run a command

inside a running container, `modal container exec --no-pty`) or `stop` (terminate it).

a list of args, e.g. `["python", "-c", "print('hi')"]`), `timeout_seconds` (default 60)

8. Manage Modal Volume (`manage_modal_volume`) — `action` is `create`, `delete`

(the volume and all its data, irreversible), or `rename`.

9. Modal Volume Files (`modal_volume_files`) — write operations on a volume's files:

`action` is `put` (upload), `get` (download), `cp` (copy inside the volume), or `rm`.

`paths` (for `cp`: sources then destination), `recursive`, `force`, `env`

10. Manage Modal Secret (`manage_modal_secret`) — `action` is `create` or `delete`.

`from_dotenv` (path), `from_json` (path), `force`, `env`. Creating requires at least

one of `key_values`, `from_dotenv`, or `from_json`.

Costs

11. Analyze Modal Costs (`analyze_modal_costs`) — read-only. Fetches

`modal billing` once and aggregates locally, so you get ranked totals and

period-over-period changes instead of hundreds of raw rows.

(`d`/`h`), `timezone`, `app`, `environment`, `top_n` (default 10), `tag_names`

`top_n` — quote it rather than summing the visible rows.

environments; `environment` filters the rows afterwards.

Secrets — inspection

12. Inspect Modal Secret (`inspect_modal_secret`) — lists the key names inside a

secret, never the values.

layer. The only way to see which keys a secret defines is to mount it in a container

and list the environment. So this tool runs `modal shell --secret ` with

`compgen -e` (a bash builtin that prints exported variable *names* only — no value is

ever printed, even inside the container), then subtracts the ~35 variables the image

and Modal runtime set anyway.

seconds (longer when the image has to build). Every other read in this server is

free; use `list_modal_resources(resource="secrets")` to see *which* secrets exist and

reach for this only when you need to know what is *inside* one.

runtime variable is still visible rather than silently dropped.

reliable choice). Pass one, e.g. `python:3.12-slim`, if your workspace's image

builder rejects that Python version.

Prompts

The server also ships four MCP prompts — multi-step workflows your client can invoke

directly (in Claude Code they appear as `/mcp__mcp-modal__`). Prompts are fetched on

demand, so unlike tools they cost nothing in per-session context:

• `debug_modal_app` (`app_name`, optional `symptom`) — an ordered triage routine: check

the app is up, search logs for tracebacks with context, fall back to the log tail,

inspect containers, then compare against deployment history and consider a rollback.

• `deploy_and_verify` (`absolute_path_to_app`, optional `env`) — confirm the target

workspace, deploy, report the live URLs, then *verify* the app is healthy instead of

assuming it.

• `review_modal_account` (optional `env`) — a read-only inventory that flags idle apps,

unexplained running containers, and orphaned volumes/secrets, naming the exact call that

would clean each one up without running it.

• `investigate_modal_costs` (optional `period`, `app`) — traces a spend increase from

the daily timeline down to the peak hour, the resource class, and the deploy or

still-running container behind it.

Output caps

Log, run, and exec output is capped before it is returned, so one chatty app can't flood

your context window. The default budget is 40,000 characters per text field (roughly 10k

tokens); when a field is trimmed the result sets `output_capped: true` and the text carries

a marker naming how much was dropped. A capped field keeps its head *and* its tail, so a

startup banner and the traceback at the end both survive.

Searching is never capped before the fact: `search_modal_logs` greps the whole fetched log

and only limits how many context blocks come back, so `match_count` is always exact.

Set `MCP_MODAL_MAX_OUTPUT_CHARS` to raise or lower the budget, or to `0` to disable capping

entirely:

{
  "mcpServers": {
    "mcp-modal": {
      "command": "uvx",
      "args": ["mcp-modal"],
      "env": { "MCP_MODAL_MAX_OUTPUT_CHARS": "80000" }
    }
  }
}

Upgrading from 0.2.x

0.3.0 replaces the 26 single-purpose tools with 10 grouped ones. Nothing was dropped — every

operation is still reachable — but the names and arguments changed:

Also new in 0.3.0: every volume tool now accepts `env` (volumes are environment-scoped, and

0.2.x silently used the default environment for file operations), `modal_volume_files`

supports `recursive` for `cp`, and `search_modal_logs`/`get_modal_logs` accept

`target="auto"`. The redundant `search` argument on the log tools is gone — use

`search_modal_logs`, which returns context instead of bare matching lines.

Response Format

All tools return responses in a standardized format, with slight variations depending on the operation type:

# Lookups (list_modal_resources):
{
    "success": True,
    "apps": [...],          # or "containers", "volumes", "contents", "secrets", ...
    "omitted_items": 0      # present when the listing was capped at 200 entries
}

# Action operations (deploy, stop, rollback, create, delete, rename, cp, put, get, rm):
{
    "success": True,
    "message": "Operation successful message",
    "command": "executed command string",
    "stdout": "command output",  # if any
    "stderr": "error output"     # if any
}

# Log / run / exec operations (snapshot-based):
{
    "success": True,
    "logs": "...",          # or "output" for run/exec
    "truncated": False,     # True when cut off at timeout_seconds
    "output_capped": False, # True when text was trimmed to fit MCP_MODAL_MAX_OUTPUT_CHARS
    "command": "executed command string"
}

# Error case (all operations):
{
    "success": False,
    "error": "Error message describing what went wrong",
    "command": "executed command string",
    "stdout": "command output",  # if available
    "stderr": "error output"     # if available
}

License

This project is licensed under the MIT License - see the LICENSE file for details.