NetworkX MCP Server

import_csv

Import a graph from a CSV edge list with columns source and target. Optionally set directed to create directed or undirected graphs for analysis.

Instructions

Import graph from CSV edge list (format: source,target per line)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "graph": "<graph>",
      "csv_data": "<csv_data>"
    },
    "name": "import_csv"
  }
}

Input Schema

Name	Required	Description	Default
`graph`	Yes
`csv_data`	Yes
`directed`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.1.0Aug 5, 2026

TDQS

B3.3/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It fails to mention whether the import replaces an existing graph, whether the graph must already exist, or any side effects. The only behavioral detail is the CSV format, which is more about parameter semantics than behavior. Significant gaps in transparency exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that directly states the core purpose and format. There is no wasted verbiage, and every word contributes to understanding. This is an example of concise, effective structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 3 parameters, no output schema, and no annotations. The description is minimal and fails to cover prerequisites, return values, or behavior beyond the basic format. It is not complete enough for an agent to fully anticipate the tool's behavior without further inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the format for csv_data ('source,target per line') but provides no information about the 'graph' parameter or the 'directed' flag. Since two of three parameters remain unexplained, the description insufficiently compensates for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Import graph from CSV edge list' with specific format details. This distinguishes it from sibling tools like add_edges or create_graph by focusing on bulk import from CSV. The verb 'import' and resource 'graph' are specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for CSV edge list imports by stating the format, but it does not explicitly contrast with alternatives like add_edges or create_graph, nor does it mention when not to use it. The guidance is implied rather than explicit, so it earns a 3.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.