csv-explorer-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| csv_inspectB | Get an overview of a CSV file including size, row/column count, detected delimiter, and a preview of the data. |
| csv_sampleC | Get sample records from a CSV file using various sampling strategies. |
| csv_schemaA | Infer the schema of a CSV file by sampling records. Returns column names, types, and nullability. |
| csv_statsA | Collect aggregate statistics for fields in a CSV file. Includes min/max, mean, median, stdDev for numeric fields, and top values for categorical fields. |
| csv_searchC | Search for records where a field matches a regex pattern. |
| csv_filterA | Filter records using query expressions. Supports comparisons (==, !=, <, >, <=, >=), text operations (contains, startswith, endswith, matches), and compound queries (AND, OR). |
| csv_validateA | Validate a CSV file for syntax errors and optionally against a schema. |
| csv_tailA | Read new records appended to a CSV file since a cursor position. Use for monitoring actively-written files. |
| csv_get_cursorA | Get the current cursor position (end of file) for use with csv_tail. |
| csv_diffC | Compare two CSV files and report differences. |
| csv_extractA | Extract a specific field value from a CSV record. Use for retrieving large/truncated field data. Can write to file for binary data (e.g., base64 images). |
| csv_large_fieldsA | List fields in a CSV that contain large values (e.g., base64 images, JSON blobs). Helps identify which fields were truncated in csv_inspect. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 12 tools
Tools are largely distinct with clear purposes. csv_search and csv_filter both retrieve matching records but differ in query syntax (regex vs expression), which could cause some initial confusion. csv_inspect and csv_schema provide different levels of overview, but descriptions clarify the difference.
All tools share the csv_ prefix and snake_case, creating a recognizable family. However, naming style is inconsistent: some use verbs (csv_filter, csv_validate), some nouns (csv_schema, csv_stats), and some adjective_noun (csv_large_fields). This slight inconsistency prevents a perfect score.
At 12 tools, the count is well-suited to the server's purpose of comprehensive CSV exploration. Each tool addresses a distinct aspect, and the count is neither sparse nor bloated.
The tool set covers the core lifecycle of CSV analysis: inspection, sampling, schema, stats, search/filter, validation, monitoring, diffing, and handling large fields. Minor gaps include lack of sorting or column manipulation, but these are beyond the apparent scope.