URL: https://gofastmcp.com/integrations/gemini-cli
Title: Gemini CLI 🤝 FastMCP - FastMCP

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Create a Server
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Gemini CLI 🤝 FastMCP
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Install and use FastMCP servers in Gemini CLI
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This integration focuses on running local FastMCP server files with STDIO transport.
For remote servers running with HTTP or SSE transport, use your client's native configuration - FastMCP's integrations focus on simplifying the complex local setup with dependencies and
uv
commands.
Gemini CLI
supports MCP servers through multiple transport methods including STDIO, SSE, and HTTP, allowing you to extend Gemini’s capabilities with custom tools, resources, and prompts from your FastMCP servers.
​
Requirements
This integration uses STDIO transport to run your FastMCP server locally. For remote deployments, you can run your FastMCP server with HTTP or SSE transport and configure it directly using Gemini CLI’s built-in MCP management commands.
​
Create a Server
The examples in this guide will use the following simple dice-rolling server, saved as
server.py
.
server.py
import
random
from
fastmcp
import
FastMCP
mcp
=
FastMCP
(
name
=
"
Dice Roller
"
)
@
mcp
.
tool
def
roll_dice
(
n_dice
:
int
)
->
list
[
int
]:
"""
Roll `n_dice` 6-sided dice and return the results.
"""
return
[
random
.
randint
(
1
,
6
)
for
_
in
range
(
n_dice
)]
if
__name__
==
"
__main__
"
:
mcp
.
run
()
​
Install the Server
​
FastMCP CLI
New in version
2.13.0
The easiest way to install a FastMCP server in Gemini CLI is using the
fastmcp install gemini-cli
command. This automatically handles the configuration, dependency management, and calls Gemini CLI’s built-in MCP management system.
fastmcp
install
gemini-cli
server.py
The install command supports the same
file.py:object
notation as the
run
command. If no object is specified, it will automatically look for a FastMCP server object named
mcp
,
server
, or
app
in your file:
# These are equivalent if your server object is named 'mcp'
fastmcp
install
gemini-cli
server.py
fastmcp
install
gemini-cli
server.py:mcp
# Use explicit object name if your server has a different name
fastmcp
install
gemini-cli
server.py:my_custom_server
The command will automatically configure the server with Gemini CLI’s
gemini mcp add
command.
​
Dependencies
FastMCP provides flexible dependency management options for your Gemini CLI servers:
Individual packages
: Use the
--with
flag to specify packages your server needs. You can use this flag multiple times:
fastmcp
install
gemini-cli
server.py
--with
pandas
--with
requests
Requirements file
: If you maintain a
requirements.txt
file with all your dependencies, use
--with-requirements
to install them:
fastmcp
install
gemini-cli
server.py
--with-requirements
requirements.txt
Editable packages
: For local packages under development, use
--with-editable
to install them in editable mode:
fastmcp
install
gemini-cli
server.py
--with-editable
./my-local-package
Alternatively, you can use a
fastmcp.json
configuration file (recommended):
fastmcp.json
{
"
$schema
"
:
"
https://gofastmcp.com/public/schemas/fastmcp.json/v1.json
"
,
"
source
"
:
{
"
path
"
:
"
server.py
"
,
"
entrypoint
"
:
"
mcp
"
},
"
environment
"
:
{
"
dependencies
"
:
[
"
pandas
"
,
"
requests
"
]
}
}
​
Python Version and Project Configuration
Control the Python environment for your server with these options:
Python version
: Use
--python
to specify which Python version your server requires. This ensures compatibility when your server needs specific Python features:
fastmcp
install
gemini-cli
server.py
--python
3.11
Project directory
: Use
--project
to run your server within a specific project context. This tells
uv
to use the project’s configuration files and virtual environment:
fastmcp
install
gemini-cli
server.py
--project
/path/to/my-project
​
Environment Variables
If your server needs environment variables (like API keys), you must include them:
fastmcp
install
gemini-cli
server.py
--server-name
"
Weather Server
"
\
--env
API_KEY=your-api-key
\
--env
DEBUG=
true
Or load them from a
.env
file:
fastmcp
install
gemini-cli
server.py
--server-name
"
Weather Server
"
--env-file
.env
Gemini CLI must be installed
. The integration looks for the Gemini CLI and uses the
gemini mcp add
command to register servers.
​
Manual Configuration
For more control over the configuration, you can manually use Gemini CLI’s built-in MCP management commands. This gives you direct control over how your server is launched:
# Add a server with custom configuration
gemini
mcp
add
dice-roller
uv
--
run
--with
fastmcp
fastmcp
run
server.py
# Add with environment variables
gemini
mcp
add
weather-server
-e
API_KEY=secret
-e
DEBUG=
true
uv
--
run
--with
fastmcp
fastmcp
run
server.py
# Add with specific scope (user, or project)
gemini
mcp
add
my-server
--scope
user
uv
--
run
--with
fastmcp
fastmcp
run
server.py
You can also manually specify Python versions and project directories in your Gemini CLI commands:
# With specific Python version
gemini
mcp
add
ml-server
uv
--
run
--python
3.11
--with
fastmcp
fastmcp
run
server.py
# Within a project directory
gemini
mcp
add
project-server
uv
--
run
--project
/path/to/project
--with
fastmcp
fastmcp
run
server.py
​
Using the Server
Once your server is installed, you can start using your FastMCP server with Gemini CLI.
Try asking Gemini something like:
“Roll some dice for me”
Gemini will automatically detect your
roll_dice
tool and use it to fulfill your request.
Gemini CLI can now access all the tools and prompts you’ve defined in your FastMCP server.
If your server provides prompts, you can use them as slash commands with
/prompt_name
.
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