"Writing about MCP" matching MCP servers:

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

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 for Durable energy trading analytics that connects Claude Desktop to Snowflake data, enabling natural-language queries about spreads, constraints, generators, and prices.

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.

Bridges Claude (or any MCP client) to manufacturing data via the i3X standard, enabling natural language queries about equipment status, hierarchy, and historical trends.

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.

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 natural language queries about grades, GPA, attendance, and schedules by connecting Claude to StudentVue school dashboards. Includes analytical tools for grade simulation, what-if scenarios, and academic performance tracking based on live school data.

Enables you to interact with your Fivetran environment through natural language, supporting read-only queries about connections and syncs, and write operations like updating sync frequency when enabled.

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 Model Context Protocol server that allows interaction with the RubyGems.org API to fetch metadata about Ruby packages, search gems, and explore dependencies and ownership information.

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

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

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

About MCP server exposing 10 APITier utility APIs as AI agent tools — email/phone/VAT validation, UK postcodes, India pincodes, barcode/QR generation, data conversion

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.

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.

Enables read-only intelligence over a Linear workspace by serving snapshot and change-history data stored in Cloudflare D1, so clients can answer questions about current work, project and milestone progress, member activity, and weekly reports without modifying Linear or invoking an LLM.

A custom MCP server that connects your investment portfolio to Poke via Plaid, enabling queries about portfolio value, holdings, and transactions.

Gives AI agents governed context about a data warehouse — table meaning, ownership, lineage, freshness, and PII flags — plus read-only, row-limited, PII-protected querying across DuckDB, Snowflake, and Databricks. Guardrails enforced at parsing, connection, and result layers keep agents from writing, running away, or leaking personal data.

Enables reading, writing, appending, and creating Google Sheets spreadsheets through MCP tools, with support for exploring spreadsheet structure and creating new sheets.

Local 395M decision model as an MCP server: pick one option from a list or answer yes/no about text, or run a recipe over a CSV, XLSX or folder. Runs offline. Apache-2.0.

Read-only MCP server exposing Android phone timeline data, including events, hourly/daily features, data coverage, and gaps, so Claude can answer questions about observed phone activity.

Enables AI agents to explore a synthetic product-event dataset and answer questions about signups, trends, funnels, and property breakdowns using a small set of composable, self-describing tools that return precomputed totals and actionable error hints.

Enables reading and writing to KoBoToolbox via MCP, including creating forms, deploying them, attaching media, and submitting data, all from chat.

Enables tracing of synthetic events through a toy Redis Streams + Postgres ingestion pipeline, answering questions about which events were dropped, duplicated, delayed, or are in flight, plus overall pipeline health. It also supports first-class fault injection and reconciles observed pipeline state against independently recorded producer ground truth to expose real loss or silent failures.

An optimized Excel MCP server with 25+ tools for creating, reading, writing, formatting, and analyzing Excel files, including pivot tables and charts, without requiring Microsoft Excel.

Enables employees to ask natural-language questions about a client's dbt semantic layer through the chatbot they already use, asking for clarification when needed, refusing when data can't answer, and logging every interaction so the semantic layer improves over time.

Enables users to load synthetic records from three finance systems, propose evidence-backed vendor matches by confidence tier, inspect crosswalk status, build reviewer packets, record human decisions, and run the eval gate, all without writing to source systems.

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.

Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.

Enables querying Excel and CSV files using SQL via natural language, allowing AI assistants to analyze data without manual SQL writing.

Databox MCP enables you to query live business metrics from 100+ data sources through AI. Ask natural language questions about marketing performance, sales data, analytics, and financial metrics to get instant insights without switching dashboards. Connect platforms like Google Ads, Salesforce, Shopify, Google Analytics, and more.

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.

Transform data structure definitions into queryable MCP servers, enabling natural language queries about field meanings, data lineage, and structure.

Enables AI assistants to interact with the Peliqan platform, providing access to hundreds of data connectors for reading and writing data in business applications.

A governance proxy for the DataHub MCP Server that enforces catalog metadata as policy, providing allow, redact, review, and deny outcomes for agent tool calls, and writing agent actions back into DataHub.