"Sway" matching MCP servers:

Enables semantic search and interaction with Fuel Network documentation and Sway Language resources within AI-powered development environments. It provides high-quality technical context using a local vector database to assist with smart contract development and FuelVM queries.

Enables aggregating multiple MCP servers behind a single HTTP/SSE endpoint, with Code Mode to reduce token usage and support for OAuth and sandboxed execution.

Enables hot-swapping llama.cpp models in a running Claude Code session via launchctl or systemd, preserving conversation context across model changes.

Enables interaction with Cloudflare D1 databases through natural language by providing tools to list tables and execute SQL queries. Uses Cloudflare's REST API for lightweight database operations without requiring direct database connections.

Enables scanning repositories for TODO and FIXME markers while avoiding false positives in strings and URLs, then reports each marker’s age, author, and staleness using git blame and history. It also counts suppression signals, long functions, and commented-out code inside real comments.

Enables AI agents to safely run test suites over MCP, returning concise JUnit-based results, trimmed tracebacks, rerun-failed support, and flaky-test detection while handling timeouts, process cleanup, and bounded output.

Enables developers and agents to determine what licenses a project's dependencies use and whether shipping is permitted, combining SPDX parsing, installed metadata, lockfile readers, a compatibility table, and a policy engine whose verdicts always carry reasons.

MCP server that provides a greeting tool to say hello to users.

Enables an AI agent to inspect which process is listening on a local port and safely plan, confirm, and verify termination of that process across platforms.

Enables an agent to mine a repository's git history and answer questions a new teammate would ask: which files are riskiest based on churn, recency and author breadth, who actually knows each file based on surviving lines, which files secretly change together, which directories depend on one person, and what recent commits mean for release notes. All analysis runs through a read-only server sandboxed to a single directory.

. A good description should be concise and describe what the server enables users to do, e.g. * Enables to interact with WordPress sites...' Then a huge block? Actually the user message includes the README content inside tags, then after the readme, there is a large block of text starting with '{

Enables an AI to risk-review Terraform and OpenTofu plan files over MCP stdio by summarizing plans, ranking dangerous changes, diffing resources with secrets masked, and comparing two plans without running Terraform.

Enables an AI agent to analyze browser HAR exports, break down request timing, identify dominant phases and critical request chains, render ASCII waterfalls, and safely redact secrets before analysis.

Enables an AI to statically lint Dockerfiles and compose files without Docker by parsing their true structure, reporting line-numbered findings with concrete fixes, and analyzing cache order, .dockerignore matching, and safe fix previews as diffs.

Enables agents to lint OpenAPI specifications and detect breaking changes between two versions of an API, normalising Swagger 2.0 and OpenAPI 3.0/3.1 into a single model with safe $ref resolution. It exposes schema-walking and example-validation tools over stdio, classifying each change as breaking, potentially breaking, or safe based on request-versus-response variance.

Enables agents to browse a catalog of OpenAPI specs, search for operations, and retrieve full operation contracts to build API requests without calling the target APIs.