"How to create charts from data" matching MCP servers:

Generates fixed-length test data records with customizable field types including strings, enums, integers, dates, and fillers. Helps developers create realistic test datasets with specified formats and constraints.

An MCP server that mocks payments, third-party API responses, and test data to enable QA flows for donation, checkout, SIP, and subscription pages without depending on a live gateway.

Enables AI agents to hire real human operators for tasks requiring physical presence, human perception, or judgment, such as verification, testing, data collection, and physical-world tasks.

Compares weekly work reports against original data to identify incorrect values, missing items, and narrative inconsistencies, providing verification results to users.

Provides an in-memory notebook interface with tools to create, retrieve, list, update, and delete notes, designed to test agent behavior through realistic MCP tool interactions.

Enables AI agents to hire verified human operators for tasks requiring physical presence, human perception, or judgment, such as real-world verification, product testing, and data collection.

Enables coding agents to read Squally CI data, including test results, flakiness, and failure diagnostics.

Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

MCP server for Seedfast, which fills PostgreSQL databases with realistic, relationally valid test data generated from live schema, providing tools for planning, running, and inspecting seeding operations.

MCP server that exposes Dira ProSuite quality verification to AI assistants, enabling data quality checks on geospatial datasets through natural language.

MCP server for managing test cases, cycles, and results in Zephyr Scale on self-hosted Jira. Enables AI agents to create, search, update, and delete test artifacts through natural language.

Enables AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

A read-only MCP server that exposes Zephyr Scale Cloud test data to review a Jira story's test coverage, answering whether tests are adequate and passing.

MCP server for measuring web performance with Google PageSpeed Insights, providing median scores with uncertainty and real-user data. It offers tools for scores, diagnostics, and comparisons to identify regressions.

MCP server that exposes the JsonFabrica API as tools, so an AI agent can generate realistic synthetic JSON test data while it codes — single documents or full relational batches from reusable templates, reproducible with a seed. Runs locally over stdio; no network service.

Run the requests in a Postman collection folder and get structured, assertion-level results back straight from your AI assistant.

Creates, validates, audits, and repairs PowerPoint .pptx files against the OOXML spec, allowing users to generate spec-compliant slides from templates.

Generate realistic relational test data with 156 field types, 22 locales, and foreign key integrity. One API call seeds your entire database.

A local-first MCP server that scores your codebase's Build Readiness by reading code and running tests on your machine, outputting a diligence-grade score and risk register without uploading your source.