"Methods to Extract Data from Files" matching MCP servers:

Read-only MCP server for querying ClickHouse (product telemetry) and Elasticsearch (download analytics), built for Percona VISTA.

MCP server that unifies real-time telemetry from industrial systems into a single queryable interface, enabling production visibility, anomaly detection, and operational insights.

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

Enables Claude Code to query fleet telemetry data for device health summaries, anomaly detection, capacity breach forecasts, and incident history via narrow MCP tools.

Enforces identity-based access control and audit logging for MCP servers, letting you grant fine-grained tool permissions to users and systems while failing secure by default.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Provides an MCP-native operational interface for diagnostics, explainability, regression checks, and operational memory on data-system internals like PostgreSQL and Databricks toy engines.

Enables AI clients to automatically investigate dbt test failures, trace root cause through BigQuery lineage, and generate plain-English incident reports.

Enables LLMs to directly query a Matomo analytics instance, execute reporting methods, fetch historical trends, report metadata, and dynamically generated chart images through typed MCP tools.

Exposes the complete Zabbix API functionality through the Model Context Protocol, mapping API methods to tools for managing hosts, triggers, and monitoring data. It enables seamless integration and control of Zabbix monitoring environments via natural language interfaces.

Enables LLMs to analyze logs by extracting patterns, redacting secrets, and providing token-efficient summaries from files, Docker containers, or journald.

Exposes configured log files as MCP tools, enabling agents to list, query, and follow logs from local and SSH sources.

Enables AI agents to analyze, cluster, compare, and export reports from local log files through seven read-only tools, returning compact evidence packs with line-number citations instead of raw log dumps. All processing happens on the local machine, so log data never leaves the environment.

Provides secure, multi-user access to Oracle Database for MCP clients, enabling SQL querying, execution, schema exploration, and performance analysis through various connection methods including TNS, JDBC, and TCPS.

Enables agents to detect drift anomalies with CUSUM, forecast trends using Holt linear methods, and automatically trip a circuit breaker to protect workflows.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

MCP server to start, monitor, search, and detect errors in logs from any project, even those without log files.

Enables querying logs and metrics with plain SQL from any MCP client via pooml's read-only query API.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.