"Expo" matching MCP servers:

Enables Claude to interact with physical iOS devices running Expo development builds via USB or network tunnels. It supports capturing screenshots, streaming system logs, managing applications, and retrieving device information through natural language.

Enables AI-powered analysis of Rapid7 vulnerability and asset data by exporting via the Bulk Export API and making it queryable through natural language or SQL in MCP-compatible tools.

Exports vulnerability and asset data from Rapid7 Command Platform via the Bulk Export API into a local DuckDB database, enabling AI assistants to run natural language queries and SQL analysis with sandboxed security.

Query your Apple Health data including sleep, heart rate, steps, workouts, and more by ingesting an exported XML archive into a local SQLite database.

Exposes the Tenable Identity Exposure (TIE) REST API as tools for LLM clients, enabling queries on security profiles, activity timelines, AD objects, and more.

Provides MCP tools to query the Tenable Identity Exposure (TIE) API for security profiles, deviances, attacks, and activity timelines, with enforced read-only mode to protect credentials.

An MCP server that lets AI agents drive App Store Connect, Google Play Console, and Expo EAS end to end — builds, listings, screenshots, privacy labels, in-app purchases, review submission and even replying to App Review. It automates roughly 60 tools so an app can go from a build to 'Waiting for Review' without clicking through two consoles.

A server for food-mediated oral exposure screening, governed contaminant and pesticide review, and version-pinned dietary evidence handoffs, converting commodity residues and consumption profiles into auditable intake summaries and PBPK-ready exports.

Enables statistical forecasting and anomaly detection over numerical time-series data using Holt linear smoothing, multi-step projections, and variance-based confidence bands.

Enables agents to forecast numerical trends with zero-dependency Holt linear exponential smoothing, multi-step horizons, variance confidence bands, and supporting statistical anomaly detection, regression, hypothesis testing, and PCA.

Enables AI clients to compute auditable vehicle export quotes with consistent decimal rules, including request normalization, funder screening, validation, comparison, and MOSS export.

Read-only MCP server exposing a filtered copy of your personal context record as one SQL surface, so assistants can query your data without the vendor owning it.

Sanitizes Continue.dev session exports and reformats them as readable Obsidian chat Markdown, with MCP tools that return only metadata (paths, counts) for privacy.

Fetches Wikipedia page wikitext via Special:Export and parses wikitables into structured rows, surfacing machine-readable warnings for structurally broken or ambiguous tables.

Enables automated GDPR/CCPA data subject access request compliance by exporting data subject profiles through OneTrust. Provides deterministic, zero-dependency MCP integration for AI agents and enterprise pipelines.

MCP server that connects AI assistants to the ExposureGuard domain security scanning API, enabling security scans, grade lookups, remediation suggestions, and dependency checks for domains.

Enables AI agents to list, inspect, and export OpenCode AI coding sessions as HTML/JSON archives with secret redaction and token statistics.

Experimental MCP server that integrates OpenAI and Serper APIs for news search, sentiment analysis, and email delivery.

Enables fault-tolerant agent tool execution with adaptive exponential backoff, full jitter, rate-limit 429 backpressure handling, and circuit breaker patterns to make AI agent calls resilient to transient failures. Plugs directly into MCP-compliant clients via JSON-RPC 2.0 stdio with zero external dependencies.

This MCP server wraps agent tool calls with fault-tolerant retry logic, including adaptive exponential backoff, full jitter, 429 rate-limit backpressure handling, and circuit breaker patterns. It enables autonomous agents to execute tools reliably without frontier LLM round-trips, using a zero-dependency Python stdio JSON-RPC interface.