Fermat MCP vs MCP Numpy
A side-by-side look at the Fermat MCP and MCP Numpy MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Fermat MCP for data science tools work; choose MCP Numpy for data science tools as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Fermat MCP when
- You need dedicated capabilities in the Data Science Tools domain.
- Its auth model fits you: No auth required.
Choose MCP Numpy when
- You need dedicated capabilities in the Data Science Tools domain.
- You prefer a local stdio subprocess transport.
- You want tools like
np_array, np_zeros, np_ones.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Data Science Tools | Data Science Tools |
| Quality signal | 48/100 · Fair | 45/100 · Fair |
| Install command | Not confirmed yet | Confirmed |
| Transport | — | Local subprocess (stdio) |
| Auth | No auth required | Not declared |
| Pricing | Free | Not declared |
| Required env vars | None listed | None listed |
Tools & capabilities
Fermat MCP tools
No tool names declared yet. Check the project README from the listing page.
MCP Numpy tools 29
np_arrayCreate a NumPy arraynp_zerosCreate zeros arraynp_onesCreate ones arraynp_fullCreate array filled with valuenp_arangeCreate array with rangenp_linspaceCreate evenly spaced arraynp_eyeCreate identity matrixnp_diagCreate diagonal arraynp_reshapeReshape arraynp_transposeTranspose arraynp_concatenateConcatenate arraysnp_splitSplit array- +17 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Fermat MCP
No confirmed install command for Fermat MCP yet — follow the setup steps linked from its listing page rather than a guessed package name.
MCP Numpy
{
"mcpServers": {
"mcp-numpy": {
"command": "uvx",
"args": [
"mcp-numpy"
]
}
}
}
Frequently asked questions
Fermat MCP is categorized under Data Science Tools and uses an install path we have not confirmed yet. MCP Numpy belongs to Data Science Tools and uses a local stdio subprocess. Pick Fermat MCP for data science tools work and MCP Numpy for data science tools.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client. Fermat MCP has no confirmed install command yet — follow its own setup instructions.
Fermat MCP is listed as free. Auth: no auth required. MCP Numpy has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add abhiphile-fermat-mcp and mcp-numpy as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Fermat MCP has a quality signal of 48/100 (Fair) with 4 views, 0 installs and 21 GitHub stars. MCP Numpy has 45/100 (Fair) with 1 views, 0 installs and 0 GitHub stars.