"Improving the Software Development Process" matching MCP servers:

A tool for SHACL-based assessment, comparison, and coverage analysis of digital passport data models, designed for AI-agent orchestration.

MCP server for Coalesce that manages nodes, pipelines, environments, jobs, and runs, and enables project validation, DDL/DML preview, deployment planning, and cloud environment application.

MCP server that archives Decent DE1 espresso shots from Visualizer.coffee into SQLite and provides analysis tools for shots, beans, and profiles via MCP.

Enables AI agents to inspect schemas, walk Delta table history, run read-only DuckDB queries, and check data-quality and job-run status safely.

Enables users to list, create, and update agencies and codelists in a Fusion Metadata Registry through MCP tools served over Streamable HTTP.

Read-only SQL across PostgreSQL, MySQL, S3-compatible buckets and folders of Parquet, CSV and JSON files — and one query can join across all of them, federated in-process by DuckDB. Sources are given as connection strings at startup, and no tool writes: they are absent rather than disabled.

An MCP server that lets Large Language Models interact with Stata software to perform regression analysis and other statistical operations.

Enables users to discover, search, validate and cross-map versioned statistical code systems — including industry, occupation, product, education and questionnaire response hierarchies — with deterministic retrieval and provenance. It supports questionnaire development, survey coding and reproducible statistical harmonisation without running any AI model inside the server.

Enables users to process large datasets record by record, supporting JSON Lines and JSON with jq expressions, with stateful navigation, result tracking, and export capabilities.

Enables MCP clients to discover processor and controller service types, build and wire Apache NiFi 2.x process groups, schedule them, and debug queues and bulletins through the NiFi REST API. Supports flow spec application, automatic canvas layout, parameter contexts, and an optional read-only mode that blocks all writes.

Enables AI agents to manage and interact with Apache NiFi through its REST API, covering process groups, processors, connections, queues, provenance, and version control via natural language tool calls.

Enables large language models to retrieve up-to-date and correct information about dlt pipelines, datasets, and schemas, improving AI-assisted development.

Give AI agents access to Formester form submissions. Read individual responses, search and filter across forms, write AI-generated insights back as custom fields, and process file attachments including PDFs and images.

Enables data engineers and BI professionals to perform data pipeline development, quality assurance, visualization, and API integration locally with AI assistance.

Enables k-anonymization of tabular data through generalization and suppression, with utility reporting and an MCP interface for field classification and anonymization. Runs entirely in-process with no network access.

MCP server that drives EViews econometrics software from Python or LLM clients via COM automation, enabling workfile creation, model estimation, diagnostics, and data exchange with pandas.

Enables the analysis of massive datasets by storing data in external variables via a sandboxed Python REPL instead of the model's context window. This allows users to process files larger than 100MB without polluting the context or hitting token limits.

Enables streaming inference over utility meter telemetry with exactly-once tumbling windows and offline, in-process anomaly detection via stdio JSON-RPC, keeping regulated meter data within the customer boundary.

A conversational copilot that guides users through the Knowledge Discovery in Databases (KDD) process to perform automated data profiling, analysis, and modeling via natural language. It enables the creation of interactive dashboards and manages the end-to-end analytical workflow within a secure sandbox environment.

Connects external APIs like Open-Meteo and AgroMonitoring to your development environment through URI-like requests, allowing access to live data directly in MCP-compatible tools.