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Fermat
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python
Language
6 months ago
First Indexed
2 months ago
Catalog Refreshed
Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"abhiphile-fermat-mcp": {
"command": "bash",
"args": [
"MCP_SERVER_ABSOLUTE_PATH/setup.sh"
]
}
}
}Fermat MCP is a dedicated server for mathematical computations, offering numerical and symbolic math, plus plotting capabilities. It helps you perform complex matrix operations, algebra, calculus, and visualization from your MCP clients in a unified, programmable way.
How to use
You connect to Fermat MCP using your MCP client with a local server configuration. The server supports multiple ways to run locally, so you can choose the method that fits your setup. Once connected, you can request numerical operations, symbolic computations, and plotting tasks through the MCP interface and receive results or plots directly.
How to install
Prepare your environment and get Fermat MCP running locally. Follow these steps in order to have a working MCP server you can connect to from clients.
# Prerequisites
# Ensure Python 3.12+ is installed
python3 --version
# Ensure uv is installed (the runtime you will use to start the server)
# Follow the uv installation instructions for your platform if you have not installed it yet
# Clone the Fermat MCP repository
git clone https://github.com/abhiphile/fermat-mcp
# Install Smithery client (optional but recommended for client setups)
npx -y @smithery/cli install @abhiphile/fermat-mcp --client gemini
You will configure MCP clients to start the local server via the provided commands. If you prefer a Bash-based startup, use the setup script from the local clone. If you prefer UVX/JIT workflows, you can run the Python server with uv as shown in your client setup.
Configuration samples you may use in your MCP client setup are shown here for quick reference. Include these exactly in your client configuration files where the tool expects an MCP server definition.
Additional content
Configuration notes and practical examples help you tailor Fermat MCP to your workflow. Below are representative configurations shown for common MCP clients. Use these exactly as-is in your client setup sections that accept MCP server definitions.
{
"mcpServers": {
"fmcp": {
"command": "bash",
"args": ["MCP_SERVER_ABSOLUTE_PATH/setup.sh"],
"description": "fmcp server is for mathematical computations, including numerical and symbolic calculations, as well as plotting."
}
}
}
If you are using Claude or the Anthropic MCP client, you can run the server with uv and specify a local directory that contains Fermat MCP. This is useful for development workflows where you clone the repository locally.
{
"mcpServers": {
"fmcp": {
"command": "uv",
"args": [
"--directory",
"/home/ty/Repositories/fermat-mcp",
"run",
"server.py"
]
}
}
}
If you use Gemini as your MCP client, place a similar configuration in your Gemini settings file. This ensures you can start the Fermat MCP server from Gemini with a single command.
{
"mcpServers": {
"fmcp": {
"command": "bash",
"args": ["MCP_SERVER_ABSOLUTE_PATH/setup.sh"],
"description": "fmcp server is for mathematical computations, including numerical and symbolic calculations, as well as plotting."
}
}
}
Available tools
plot_barchart
Plots bar charts from given data values.
plot_scatter
Creates scatter plots from data points.
plot_chart
Plots line, scatter, or bar charts.
plot_stem
Creates stem plots for discrete data.
plot_stack
Generates stacked area or bar charts.
eqn_chart
Plots mathematical equations.
add
Basic addition operation in numeric arrays or matrices.
sub
Basic subtraction operation.
mul
Basic multiplication operation.
div
Basic division operation.
power
Exponentiation operation.
abs
Absolute value operation.
exp
Exponential function.
log
Natural or base-specific logarithm.
sqrt
Square root operation.
sin
Sine function.
cos
Cosine function.
tan
Tangent function.
mean
Compute the mean of an array.
median
Compute the median of an array.
std
Compute the standard deviation.
var
Compute the variance.
min
Find the minimum value.
max
Find the maximum value.
argmin
Index of the minimum value.
argmax
Index of the maximum value.
percentile
Compute specified percentile.
dot
Dot product between two arrays.
matmul
Matrix multiplication.
inv
Matrix inverse.
det
Matrix determinant.
eig
Eigenvalues computation.
solve
Solve linear systems.
svd
Singular value decomposition.
create
Create a new matrix.
zeros
Create a zero-filled matrix.
ones
Create a ones-filled matrix.
full
Create a matrix filled with a constant value.
arange
Create a range of numbers.
linspace
Create linearly spaced numbers.
reshape
Reshape an array.
flatten
Flatten an array.
concatenate
Concatenate arrays.
transpose
Transpose a matrix.
stack
Stack arrays.
simplify
Algebraic simplification of expressions.
expand
Expand algebraic expressions.
factor
Factor polynomials.
collect
Collect like terms in expressions.
diff
Differentiate expressions.
integrate
Integrate expressions.
limit
Compute limits.
series
Compute series expansions.
solve
Solve algebraic equations.
solveset
Solve equations symbolically.
linsolve
Solve linear systems symbolically.
nonlinsolve
Solve nonlinear systems.
create_matrix
Create a matrix structure from given data.
det_matrix
Compute determinant of a matrix.
rref
Compute reduced row echelon form.
eigenvals
Compute eigenvalues of a matrix.