"Learning or Writing Code in Python" matching MCP servers:

Enables agents to connect to Kafka clusters, discover topics and consumer groups, draft and activate a catalog describing what events carry, inspect stuck or at-risk value, and optionally redrive dead letters after a dry run.

Enables LLMs to query live data from over 250+ sources via CData Python Connectors using natural language. Wraps connectors as a Model Context Protocol server.

Enables training and comparing machine-learning models, generating predictions and SHAP explanations, evaluating performance, selecting the best model, and exporting Parquet audit logs through MCP tools.

A comprehensive educational server demonstrating Model Context Protocol capabilities for tools, resources, and prompts, allowing AI assistants to connect to external data and functionality.

Enables training and evaluating Logistic Regression and KNN models on breast cancer data, making predictions, selecting the best model, generating SHAP explanations, and exporting Parquet audit logs through MCP tools.

Enables training, evaluating, selecting, and explaining Logistic Regression and KNN models, making predictions, and exporting Parquet audit logs through MCP tools.

A cryptocurrency price service that provides real-time crypto pricing information through an MCP (Model Context Protocol) framework with CoinMarketCap API integration.

MCP server for configuring the konsol Frappe app via the CLI. Enables AI clients to manage dimensions, measures, fact tables, connectors, and schemas using natural language.

Enables AI assistants to load CSV datasets, compute summary statistics, filter rows, rank columns, and compute correlations through the Model Context Protocol.

A resilient MCP server wrapping FiinQuant/FiinQuantX Python SDK for Claude Desktop and Cursor, providing market data, fundamental analysis, screening, and technical indicators via stdio with timeouts, error envelopes, and free-tier guards.

MCP server providing seamless integration with Trino and Iceberg for advanced data exploration, querying, and table maintenance.

Enables LLM agents to query governed GA4 metrics over MCP, returning definitions, assumptions, and failure modes from a MetricFlow semantic layer without writing SQL.

MCP server that exposes local Python scripts as tools for AI clients (e.g. Claude Desktop), enabling directory tree generation, Excel-to-text conversion, Python code extraction, and text file merging.

MCP server for converting OEM energy telemetry payloads into ODS-E records and validating them via the odse Python package.

A Model Context Protocol server that lets LLM clients answer business questions in natural language over a Databricks dataset without writing SQL by hand.

Enables auditing spending history to find transactions with missing or questionable categories and getting ranked, history-based category candidates for confirmation. Also supports writing approved category fixes back and importing missing transactions from bank statements, with preview-by-default writes.

Enables AI agents to list metrics and dimensions, inspect definitions, and run governed metric queries against Apache Iceberg tables through a semantic layer, without writing SQL or accessing raw rows or columns outside their role.

Enables reading and writing Excel workbooks (.xlsx) through MCP. Supports listing sheets, tables, pivot tables, reading cell data, exporting to CSV/text/Markdown, and creating/modifying Excel files.

AI-powered MCP server for connecting and managing Jupyter Notebooks. Enables interactive code execution, multi-notebook management, and multimodal output for data analysis, visualization, and machine learning.

Enables auditing of .xlsx workbooks locally and read-only, flagging formula errors, broken references, inconsistent formulas, typed-over values and other risks through both static checks and an independent Python recalculation engine, with tools to run a full audit or inspect a single cell.

Enables language models to model SAP BW/4HANA through the BW Modeling Tools REST interface, with intent-based tools for searching, reading, writing, activating, querying data, monitoring, runtime actions, and transports. It uses compact schemas and safe-by-default permissions to complete changes in few calls.

Enables querying, inserting, and managing unstructured data in RawTree via SQL, JSON ingestion, and log inspection through MCP clients like Claude Code, Cursor, and Claude Desktop.

A small Python MCP server that lets Cursor's agent browse databases and tables, inspect columns, run read-only SQL, and register new sources or cache tables against a Zetaris instance. It is paired with a project rule that steers the agent to do all its data work through this server rather than going around it.

A Model Context Protocol server that provides Claude with access to InfluxDB time-series database instances, enabling data writing, querying, and management of organizations and buckets through natural language.

A Python MCP server for hypothesis-driven data analysis, managing analysis designs, data catalogs, and review workflows through Claude Code or any MCP-compatible client.

Provides comprehensive Formula 1 data access including race schedules, session results, lap times, telemetry data, driver/constructor standings, and circuit information. Enables users to retrieve and analyze F1 racing data through natural language queries using the FastF1 Python package.

Enables AI assistants to control any Odoo database via XML-RPC, with features for reading, writing, importing/exporting data, and generating intervention reports.

Declarative BIM and Building-as-Code engine for AI agents: model buildings in YAML, compute deterministic QTO and cost estimations, compile to IFC4, and view interactive 3D WebGL models.

An MCP server that provides data visualization and machine learning tools, featuring automated intent-based pipeline routing for data cleaning and model training. It enables LLMs to process CSV or JSON data to generate visual charts, perform regressions, or execute clustering analysis.

A FastMCP server for natural language data analysis that allows users to load CSV files, execute Python code with pandas and numpy, and generate matplotlib visualizations. It provides a suite of tools for data exploration, statistical summaries, and querying datasets through MCP-compatible clients.

A Model Context Protocol (MCP) server that provides tools for reading Excel (xlsx) files, enabling extraction of data from entire workbooks or specific sheets with results returned in structured JSON format.

A Python MCP server that retrieves requirements and bug data from TAPD platform to provide AI clients with project management information.

Enables AI to analyze and transform data using fusion algorithms with statistical, machine learning, or hybrid methods. Provides seamless data format conversion and enhanced analytical capabilities through the Model Context Protocol.

MCP server for reading and writing data files (Excel, PDF, CSV, JSON, text) with safe write rules and provenance tracking.

A Python MCP server that lets you manage Microsoft Fabric through natural language in Claude Code or Claude Desktop, with 77+ tools covering workspaces, lakehouses, warehouses, SQL, DAX, semantic models, notebooks, pipelines, OneLake, and Microsoft Graph.

Converts PDF, Word, PowerPoint, Excel, and HTML documents into Markdown, handling files up to 8 MB in a single call and routing larger or scanned files through an OCR and table-detection queue that returns Markdown plus a JSON structure file. Results arrive either by polling or a signed webhook.

Enables an AI assistant to load IBM Maximo data into a local staging sheet, propose and diff changes, and require human approval before writing to Maximo, while relaying MCP requests without cloud storage or telemetry.

Connects MCP clients such as Claude Desktop and Claude Code to Opteryx so users can ask questions about their data in plain English, discovering datasets, reading schemas, running queries, profiling columns, and validating SQL. Every call runs as the token's own user and against only the data that user can see.

Enables AI clients to access realtime quotes and K-line data from a running MyQuant terminal, including connectivity checks, symbol normalization, and historical/recent K-line queries. It bridges the terminal's Python SDK to MCP-compatible clients for technical analysis and review workflows.

An MCP server for reading, writing, and analyzing Excel files using Python, pandas, and openpyxl. It enables tasks such as managing multiple worksheets, performing structural data analysis, and creating new files from JSON data.