mpl_mcp_plot_barchart
Plots barchart of given datavalues
LABSCO SUMMARY
NumPy, SymPy and Matplotlib reachable as tools instead of as a scratch script.
The symbolic half is what matters: an integral or an eigenvalue comes back computed by SymPy rather than recalled, and the plotting tools then draw whatever you just worked out.
What it is
A FastMCP server in three parts: Matplotlib plotting, NumPy numeric work, and SymPy symbolic algebra and calculus.
What you get
- Plots: line, scatter and bar charts, stem plots for discrete data, stacked area and bar charts
- Mathematical equations plotted directly
- NumPy operations: arithmetic, trigonometry, statistics, linear algebra, matrix creation, array reshaping
- SymPy algebra: simplify, expand, factor, collect
- Calculus: differentiate, integrate, limits, series
- Equation solving: solve, solveset, linsolve, nonlinsolve
- Matrix work in both libraries — determinant, inverse, eigenvalues, rref, svd
Requirements
Python 3.12 or higher and uv. Cloned from the repository and launched through its setup.sh from the client config.
Setup effort
Build from source
USE CASES
01
Checking an integral or derivative you did by hand
diff, integrate, limit and series run in SymPy, so the result is computed rather than remembered.
02
Seeing the function you are reasoning about
Plot the equation itself rather than sampling it into points first.
03
Charting data you have just produced
Line, bar and scatter from the same values, so you can try the shape that reads best.
04
Solving a system of equations
solve, solveset, linsolve and nonlinsolve are all exposed, alongside matrix determinant, inverse, rref and eigenvalues.
05
Showing a discrete or cumulative series properly
Stem plots for discrete data, stacked area or bar charts for parts of a whole.
12 tools
Listed in project code.
mpl_mcp_plot_scatter
Plots scatter chart of given datavalues
mpl_mcp_plot_chart
Plots line/scatter/bar chart of given datavalues
mpl_mcp_plot_stem
Plots stem chart of given datavalues
mpl_mcp_plot_stack
Plots stacked area/bar chart of given datavalues
mpl_mcp_eqn_chart
Plots mathematical equations
numpy_mcp_numerical_operation
Do numerical operation like add, sub, mul, div, power, abs, exp, log, sqrt, sin, cos, tan, mean, median, std, var, min, max, argmin, argmax, percentile, dot, matmul, inv, det, eig, solve, svd
numpy_mcp_matlib_operation
Do matrix operations: rand-mat, zeros, ones, eye, identity, arange, linspace, reshape, flatten, concatenate, transpose, stack
sympy_mcp_algebra_operation
Do algebraic operations like simplify, expand, factor, collect
sympy_mcp_calculus_operation
Do calculus operations like diff, integrate, limit, series
sympy_mcp_equation_operation
Do symbolic equation operations like solve, solveset, linsolve, nonlinsolve
sympy_mcp_matrix_operation
Do symbolic matrix operations like create, det, inv, rref, eigenvals
BEFORE YOU INSTALL
What to know first
Tools you get
12 tools registered in the project's code.
Requires
- bash on PATH
- uv on PATH
- Python 3.12 or later
INSTALLATION
Connect your client
Server setup
TERMINAL
git clone https://github.com/abhiphile/fermat-mcpMCP Clients
VS Code
VS CODE · JSON
{
"servers": {
"fmcp": {
"command": "bash",
"args": [
"<YOUR_MCP_SERVER_ABSOLUTE_PATH>/setup.sh"
],
"description": "fmcp server is for mathematical computations, including numerical and symbolic calculations, as well as plotting."
}
}
}<YOUR_MCP_SERVER_ABSOLUTE_PATH> is the full path of the fermat-mcp folder that git clone created. setup.sh creates a uv virtual environment, installs the dependencies and starts the server.
Windsurf, Gemini CLI
JSON
{
"mcpServers": {
"fmcp": {
"command": "bash",
"args": [
"<YOUR_MCP_SERVER_ABSOLUTE_PATH>/setup.sh"
],
"description": "fmcp server is for mathematical computations, including numerical and symbolic calculations, as well as plotting."
}
}
}<YOUR_MCP_SERVER_ABSOLUTE_PATH> is the full path of the fermat-mcp folder that git clone created. setup.sh creates a uv virtual environment, installs the dependencies and starts the server.
Claude Desktop
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"fmcp": {
"command": "uv",
"args": [
"--directory",
"<YOUR_MCP_SERVER_ABSOLUTE_PATH>",
"run",
"server.py"
]
}
}
}<YOUR_MCP_SERVER_ABSOLUTE_PATH> is the full path of the fermat-mcp folder that git clone created.
Gemini CLI — Smithery
GEMINI CLI — SMITHERY · TERMINAL
npx -y @smithery/cli install @abhiphile/fermat-mcp --client gemini
