io.github.daedalus/mcp-numpy
PYPI · MCP-NUMPY · SCANNED SEP 20
An MCP server that exposes NumPy functionality
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security50
- Malware scan not yet available for this package.Unverified
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 1 of 16 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 174 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability80
- AI-judged instruction clarity (excellent).Pass
- Tool/resource definitions use about 3263 tokens (~45/item across 72 items; 72 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
- Stability not yet verified: two runs of the same published version returned different tool surfaces, so we cannot tell a change in the package from a difference in our own sandbox run.Unverified
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 99% of tool parameters carry a description.Partial
- Structured output schemas are declared (28% of tools); any adoption earns full credit.Pass
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "np_squeeze" implies "remove" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 72 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
How do I install the io.github.daedalus/mcp-numpy server?
io.github.daedalus/mcp-numpy runs locally as a PyPI package, launched with uvx mcp-numpy. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · mcp-numpy
claude mcp add daedalus-mcp-numpy -- uvx mcp-numpy
{
"mcpServers": {
"daedalus-mcp-numpy": {
"command": "uvx",
"args": [
"mcp-numpy"
]
}
}
} {
"servers": {
"daedalus-mcp-numpy": {
"command": "uvx",
"args": [
"mcp-numpy"
]
}
}
} codex mcp add daedalus-mcp-numpy -- uvx mcp-numpy
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"daedalus-mcp-numpy": {
"type": "local",
"command": [
"uvx",
"mcp-numpy"
],
"enabled": true
}
}
} openclaw mcp add daedalus-mcp-numpy --command uvx --arg mcp-numpy
mcp_servers:
daedalus-mcp-numpy:
command: "uvx"
args: ["mcp-numpy"] {
"McpServers": {
"daedalus-mcp-numpy": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"mcp-numpy"
]
}
}
} assistant mcp add daedalus-mcp-numpy -t stdio -c uvx -a mcp-numpy
{
"mcpServers": {
"daedalus-mcp-numpy": {
"command": "uvx",
"args": [
"mcp-numpy"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 20 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 19 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 17 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 15 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 14 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 12 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 11 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 9 Sept 26 −13
- Stability: 0.90 → unverified ▼ security
- Tool coverage: 100% → 28% ▼ functional
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 20 Sept 2026 · Analysed pypi/mcp-numpy@0.1.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 16 packages
| Packages resolved | 16 |
|---|---|
| Stale | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
np_reshape Np Reshape ~48
Give a new shape to an array without changing its data.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array to reshape. |
| newshape | – | yes | The new shape (int or list of ints). |
No output schema declared.
No examples provided.
np_shape Np Shape ~25
Return the shape of an array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_shuffle Np Shuffle ~30
Modify a sequence in-place by shuffling its contents.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The array to shuffle. |
No output schema declared.
No examples provided.
np_sin Np Sin ~30
Trigonometric sine, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array (in radians). |
No output schema declared.
No examples provided.
np_sinh Np Sinh ~27
Hyperbolic sine, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_size Np Size ~28
Return the total number of elements in an array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| Name | Type | Req | Description |
|---|---|---|---|
| result | integer | yes | – |
No examples provided.
np_solve Np Solve ~46
Solve a linear matrix equation, or system of linear equations.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | Coefficient matrix. |
| b | array | yes | Ordinate or "dependent variable" values. |
No output schema declared.
No examples provided.
np_split Np Split ~73
Split an array into multiple sub-arrays.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The array to split. |
| axis | integer | – | The axis along which to split (default: 0). |
| indices_or_sections | – | yes | If an int, the number of equal sections. If a list, the indices at which to split. |
No output schema declared.
No examples provided.
np_sqrt Np Sqrt ~31
Return the non-negative square root of an array element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_squeeze Np Squeeze ~49
Remove single-dimensional entries from the shape of an array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Selects a subset of the length-1 dimensions (default: all). |
No output schema declared.
No examples provided.
np_std Np Std ~65
Compute the standard deviation along the specified axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Axis along which to compute std (default: None, std of all). |
| ddof | integer | – | Delta degrees of freedom for normalization (default: 0). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_subtract Np Subtract ~36
Element-wise subtraction of two arrays.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | First input array. |
| b | array | yes | Second input array. |
No output schema declared.
No examples provided.
np_sum Np Sum ~63
Sum of array elements over given axis(es).
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Axis along which to sum (default: None, sums all). |
| dtype | string | – | The type of the returned array (default: "float64"). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_svd Np Svd ~43
Singular Value Decomposition.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| full_matrices | boolean | – | Whether to compute full SVD (default: False). |
Structured output declared, but exposes no named fields.
No examples provided.
np_tan Np Tan ~30
Trigonometric tangent, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array (in radians). |
No output schema declared.
No examples provided.
np_tanh Np Tanh ~27
Hyperbolic tangent, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_tile Np Tile ~46
Construct an array by repeating the input array the given number of times.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array to tile. |
| reps | – | yes | The number of repetitions along each axis. |
No output schema declared.
No examples provided.
np_trace Np Trace ~55
Return the sum along the main diagonal of the array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array (must be at least 2D). |
| offset | integer | – | The diagonal offset (default: 0, main diagonal). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | number | yes | – |
No examples provided.
np_transpose Np Transpose ~47
Reverse or permute the axes of an array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axes | – | – | By default, reverse the axes. Otherwise, permute the axes. |
No output schema declared.
No examples provided.
np_var Np Var ~64
Compute the variance along the specified axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Axis along which to compute variance (default: None, variance of all). |
| ddof | integer | – | Delta degrees of freedom for normalization (default: 0). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_zeros Np Zeros ~55
Create an array of zeros.
| Name | Type | Req | Description |
|---|---|---|---|
| dtype | string | – | The data type of the array (default: "float64"). |
| shape | – | yes | An integer for 1D shape, or a list of integers for multi-dimensional. |
No output schema declared.
No examples provided.
npastype Npastype ~39
Copy of the array, cast to a specified type.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| dtype | string | yes | The target dtype. |
No output schema declared.
No examples provided.
What is the io.github.daedalus/mcp-numpy server?
io.github.daedalus/mcp-numpy is listed in the public MCP registry as io.github.daedalus/mcp-numpy. An MCP server that exposes NumPy functionality. This page covers its PyPI package (mcp-numpy).
Is the io.github.daedalus/mcp-numpy server safe to use?
io.github.daedalus/mcp-numpy scores 55 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.daedalus/mcp-numpy server expose?
io.github.daedalus/mcp-numpy exposes 72 tools: np_array, np_zeros, np_ones, np_full, np_arange, and 67 more. Their descriptions and schemas cost roughly 3,263 tokens of context every time the server is loaded.
Is the io.github.daedalus/mcp-numpy server still maintained?
io.github.daedalus/mcp-numpy is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the io.github.daedalus/mcp-numpy server under?
io.github.daedalus/mcp-numpy declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.