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_abs Np Abs ~26
Calculate the absolute value of array elements.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_add Np Add ~35
Element-wise addition 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_arange Np Arange ~78
Create an array with evenly spaced values within a given interval.
| Name | Type | Req | Description |
|---|---|---|---|
| dtype | string | – | The data type of the array (default: "float64"). |
| start | number | yes | Start of interval. |
| step | number | – | Spacing between values (default: 1). |
| stop | number | yes | End of interval (exclusive). |
No output schema declared.
No examples provided.
np_arccos Np Arccos ~36
Inverse cosine, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array (must be in [-1, 1]). |
No output schema declared.
No examples provided.
np_arcsin Np Arcsin ~36
Inverse sine, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array (must be in [-1, 1]). |
No output schema declared.
No examples provided.
np_arctan Np Arctan ~27
Inverse tangent, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_argmax Np Argmax ~48
Return the indices of the maximum values along an axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Axis along which to find argmax (default: None, flattened). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_argmin Np Argmin ~48
Return the indices of the minimum values along an axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Axis along which to find argmin (default: None, flattened). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_array Np Array ~73
Create a NumPy array from a list.
| Name | Type | Req | Description |
|---|---|---|---|
| data | array | yes | A Python list containing the array elements. |
| dtype | string | – | The data type of the array (default: "float64"). Common values: "int32", "int64", "float32", "float64", "complex128". |
No output schema declared.
No examples provided.
np_concatenate Np Concatenate ~51
Join a sequence of arrays along an existing axis.
| Name | Type | Req | Description |
|---|---|---|---|
| arrays | array | yes | A sequence of arrays to concatenate. |
| axis | integer | – | The axis along which to concatenate (default: 0). |
No output schema declared.
No examples provided.
np_corrcoef Np Corrcoef ~58
Return Pearson product-moment correlation coefficients.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | A 1-D or 2-D array containing multiple variables and observations. |
| rowvar | boolean | – | If True, each row represents a variable (default: True). |
No output schema declared.
No examples provided.
np_correlate Np Correlate ~66
Cross-correlation of two 1-dimensional sequences.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | First input sequence. |
| b | array | yes | Second input sequence. |
| mode | string | – | Computation mode (default: "full"). Options: "full", "same", "valid". |
No output schema declared.
No examples provided.
np_cos Np Cos ~29
Trigonometric cosine, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array (in radians). |
No output schema declared.
No examples provided.
np_cosh Np Cosh ~27
Hyperbolic cosine, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_cross Np Cross ~36
Compute the cross product 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_cumprod Np Cumprod ~51
Return the cumulative product of the array along a given axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | The axis along which to compute cumprod (default: None, flattened). |
No output schema declared.
No examples provided.
np_cumsum Np Cumsum ~50
Return the cumulative sum of the array along a given axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | The axis along which to compute cumsum (default: None, flattened). |
No output schema declared.
No examples provided.
np_det Np Det ~29
Compute the determinant of an array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input matrix (must be square). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | number | yes | – |
No examples provided.
np_diag Np Diag ~61
Create a diagonal array or extract the diagonal of an array.
| Name | Type | Req | Description |
|---|---|---|---|
| dtype | string | – | The data type of the array (default: "float64"). |
| k | – | yes | If a list, creates diagonal array from it. If an int, extracts that diagonal. |
No output schema declared.
No examples provided.
np_diff Np Diff ~67
Calculate the n-th discrete difference along the given axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | integer | – | The axis along which to difference (default: 0). |
| n | integer | – | The number of times values are differenced (default: 1). |
No output schema declared.
No examples provided.
np_divide Np Divide ~42
Element-wise division of two arrays.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | First input array (dividend). |
| b | array | yes | Second input array (divisor). |
No output schema declared.
No examples provided.
np_dot Np Dot ~36
Compute the dot product of two arrays.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | First input array. |
| b | array | yes | Second input array. |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_dtype Np Dtype ~25
Return the dtype of an array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
np_eig Np Eig ~32
Compute the eigenvalues and eigenvectors of a square array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input square matrix. |
Structured output declared, but exposes no named fields.
No examples provided.
np_exp Np Exp ~28
Calculate the exponential of all elements in the array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_eye Np Eye ~47
Return a 2D identity array.
| Name | Type | Req | Description |
|---|---|---|---|
| dtype | string | – | The data type of the array (default: "float64"). |
| m | – | – | – |
| n | integer | yes | – |
No output schema declared.
No examples provided.
np_flatten Np Flatten ~27
Return a flattened copy of the array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_full Np Full ~72
Create an array filled with a constant value.
| Name | Type | Req | Description |
|---|---|---|---|
| dtype | string | – | The data type of the array (default: "float64"). |
| fill_value | number | yes | The value to fill the array with. |
| shape | – | yes | An integer for 1D shape, or a list of integers for multi-dimensional. |
No output schema declared.
No examples provided.
np_histogram Np Histogram ~63
Compute the histogram of a set of data.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | Input data. |
| bins | – | – | Number of bins or bin edges (default: 10). |
| range | – | – | The lower and upper range of the bins (default: [min, max]). |
Structured output declared, but exposes no named fields.
No examples provided.
np_inv Np Inv ~37
Compute the (multiplicative) inverse of a matrix.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input matrix (must be square and invertible). |
No output schema declared.
No examples provided.
np_linalg_norm Np Linalg Norm ~76
Matrix or vector norm.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| ord | string | – | The order of the norm (default: "fro" for matrices, "2" for vectors). Common values: "fro", "nuc", "inf", "-inf", "0", "1", "2". |
| Name | Type | Req | Description |
|---|---|---|---|
| result | number | yes | – |
No examples provided.
np_linspace Np Linspace ~77
Create an array with evenly spaced numbers over a specified interval.
| Name | Type | Req | Description |
|---|---|---|---|
| dtype | string | – | The data type of the array (default: "float64"). |
| num | integer | – | Number of samples to generate (default: 50). |
| start | number | yes | Start of interval. |
| stop | number | yes | End of interval. |
No output schema declared.
No examples provided.
np_log Np Log ~25
Natural logarithm, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_log10 Np Log10 ~28
Base-10 logarithm, element-wise.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
No output schema declared.
No examples provided.
np_matmul Np Matmul ~41
Matrix product of two arrays.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | First input array (2D). |
| b | array | yes | Second input array (2D). |
No output schema declared.
No examples provided.
np_max Np Max ~49
Return the maximum of an array or maximum along an axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Axis along which to find maximum (default: None, max of all). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_mean Np Mean ~46
Compute the arithmetic mean along the specified axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Axis along which to compute mean (default: None, mean of all). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_min Np Min ~49
Return the minimum of an array or minimum along an axis.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | Axis along which to find minimum (default: None, min of all). |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_mod Np Mod ~41
Element-wise modulo of two arrays.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | First input array (dividend). |
| b | array | yes | Second input array (divisor). |
No output schema declared.
No examples provided.
np_multiply Np Multiply ~36
Element-wise multiplication 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_ndim Np Ndim ~28
Return the number of dimensions of an array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| Name | Type | Req | Description |
|---|---|---|---|
| result | integer | yes | – |
No examples provided.
np_ones Np Ones ~55
Create an array of ones.
| 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.
np_percentile Np Percentile ~51
Compute the q-th percentile of the array elements.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| q | – | yes | Percentile(s) to compute (0-100). Can be a float or list. |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_power Np Power ~39
Element-wise exponentiation of array elements.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | The base array. |
| b | – | yes | The exponent (can be array or scalar). |
No output schema declared.
No examples provided.
np_quantile Np Quantile ~52
Compute the q-th quantile of the array elements.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| q | – | yes | Quantile(s) to compute (0-1). Can be a float or list. |
| Name | Type | Req | Description |
|---|---|---|---|
| result | – | yes | – |
No examples provided.
np_rand Np Rand ~31
Random values in a given shape.
| Name | Type | Req | Description |
|---|---|---|---|
| shape | – | yes | The shape of the output (int or list of ints). |
No output schema declared.
No examples provided.
np_randint Np Randint ~80
Return random integers from low (inclusive) to high (exclusive).
| Name | Type | Req | Description |
|---|---|---|---|
| high | – | – | Upper bound (exclusive). If None, low=0 and this becomes high. |
| low | integer | yes | Lowest integers to be drawn (inclusive). If high is None, this is the upper bound. |
| size | – | – | Output shape (int or tuple of ints). |
No output schema declared.
No examples provided.
np_randn Np Randn ~40
Return a sample (or samples) from the "standard normal" distribution.
| Name | Type | Req | Description |
|---|---|---|---|
| shape | – | yes | The shape of the output (int or list of ints). |
No output schema declared.
No examples provided.
np_random_choice Np Random Choice ~65
Generates a random sample from a given array.
| Name | Type | Req | Description |
|---|---|---|---|
| a | array | yes | 1-D array-like object from which to sample. |
| replace | boolean | – | Whether sampling with replacement (default: True). |
| size | – | – | Output shape (default: None, returns single value). |
No output schema declared.
No examples provided.
np_repeat Np Repeat ~56
Repeat elements of an array.
| Name | Type | Req | Description |
|---|---|---|---|
| array | array | yes | The input array. |
| axis | – | – | The axis along which to repeat values (default: flattens). |
| repeats | integer | yes | The number of repetitions for each element. |
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.