"Searching PubMed references and formatting them in Markdown" matching MCP servers:

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

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 users to convert a vendor partner directory (such as PartnerPage or the Shopify Partner Directory) or a trade body member list into one company row per listing, each carrying website, domain, tier, tags, and location for Clay-ready output. It runs the extraction on Apify, returning dataset rows for up to 20 directory URLs with optional deduping, detail enrichment, and a cost cap.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

Converts, aligns, reshapes, and inspects tabular data across Markdown, CSV, TSV, JSON, and HTML with CJK-aware alignment and deterministic transformations, entirely offline and without file access.

Converts PDF, DOCX, PPTX, XLSX, CSV, and JSON into clean, compact, AI-ready Markdown, reducing tokens up to 65%.

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.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

Enables fetching any public web page through managed proxies, with optional JavaScript rendering, returning markdown, text, HTML, or structured JSON.

Enables AI agents to work with a real Excel-compatible spreadsheet engine, allowing them to create and manipulate structured data blocks, write and evaluate formulas, and save genuine .xlsx files with live formulas for human verification and reuse.

Generates formatted Excel (.xlsx) files from user requests and deposits them into Cleyrop project data.

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

Enables local, read-only product-data checks for reviewing product records, comparing feed snapshots, and comparing dimensions against source rules, returning match or hold decisions without fetching references or modifying feeds.

Converts PDF bank statements into structured data (Markdown, JSON, CSV, JSONL) with verified transactions and balance checks, enabling agents to audit numbers.

An MCP server that exposes Akahu (New Zealand open-banking) data to LLM agents, allowing them to list bank accounts, inspect investment holdings, and pull transactions for analysis.

Enables MCP clients to analyze contact exports, identify duplicate people with evidence-based matching, merge them into a cleaned CSV, and report every conflicting value.

Enables AI agents and their users to ask business questions in plain language and receive governed metric values, breakdowns, share-of-total figures, and the exact parameterized SQL behind them, drawn from a single semantic model rather than ad-hoc SQL. It also lets clients inspect available metrics and their definitions, and preview optimized queries without executing them.

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 users to clean and de-duplicate sales lead lists locally without API keys or network calls. It normalizes names, emails, phone numbers, and website domains, drops invalid emails, removes duplicate leads by email, and validates email formatting.

An MCP server that allows AI models to create data visualizations using Vega-Lite syntax by providing tools to save data tables and generate visualizations from them.

Enables comparison of supplied supplier or vendor statement open items against an accounts payable ledger, identifying missing items, amount and date discrepancies, and ambiguous repeated references with exact reference evidence.

Enables users to review a supplied batch of supplier invoices or vendor bills for repeated references, normalized reference variations, and identical amount-and-date candidates, returning grouped evidence and exact review reasons from local history. Supports saved reports, CSV export, and use with MCP clients such as Claude Desktop, Claude Code, and Cursor.