Vector distance

vector-distance · version 1.0.0 · Vectors & matrices · free, no key needed

Compute the Euclidean, Manhattan, or Chebyshev distance between two equal-length finite-number vectors.

Use when you need to: vector distance · euclidean distance · manhattan distance.

Supported

• vector distance
• euclidean distance
• manhattan distance
• chebyshev distance

Not supported

• vectors of different lengths
• Minkowski distance with arbitrary p
• geographic/geodesic distance

Behavior

• Inputs a and b are arrays of finite JSON numbers with the same length, from 1 to 64 entries, magnitude bounded to at most 1000000.
• Optional input metric selects euclidean (default, L2 of the difference), manhattan (L1 of the difference), or chebyshev (L-infinity of the difference).
• Computed with IEEE-754 double-precision arithmetic; the euclidean metric uses Math.sqrt and is rounded to double precision, not exact.
• The result is always non-negative; -0 is normalized to 0.

Input

• a (array of number, required): min items 1; max items 64
• b (array of number, required): min items 1; max items 64
• metric (one of "euclidean", "manhattan", "chebyshev", optional)

Output

• result (number, required)

Limits

• max dim: 64
• max abs value: 1000000

Example

Request input:

{
  "a": [
    0,
    0
  ],
  "b": [
    3,
    4
  ]
}

Response:

{
  "result": {
    "result": 5
  }
}

How to call it

MCP

Connect https://computefirst.net/mcp (setup), then call execute with:

{
  "id": "vector-distance",
  "version": "1.0.0",
  "input": {
    "a": [
      0,
      0
    ],
    "b": [
      3,
      4
    ]
  }
}

HTTP (no key)

curl -X POST https://computefirst.net/v1/tools/vector-distance/versions/1.0.0/execute \
  -H "Content-Type: application/json" \
  -d '{"a":[0,0],"b":[3,4]}'

The machine-readable contract is at /v1/tools/vector-distance/versions/1.0.0.

CLI

node cli.mjs run vector-distance 1.0.0 --input input.json --base-url https://computefirst.net

Get the client at /clients/cli/.

Related tools

• Vector norm: Compute the L1, L2 (Euclidean), or L-infinity (Chebyshev) norm of a finite-number vector.
• Matrix vector multiply: Multiply an MxN finite-number matrix by a length-N finite-number vector, producing a length-M vector.
• Vector add: Add two equal-length finite-number vectors elementwise.
• Vector angle: Compute the angle in radians between two equal-length finite-number vectors.
• Vector approx equal: Compare two equal-length finite-number vectors for approximate equality within an absolute tolerance.
• Vector cross: Compute the 3-dimensional cross product of two finite-number vectors.