"Information on Fake News" matching MCP servers:

Enables AI coding agents to inspect GitHub repositories and shell commands for download-and-execute payloads, obfuscation, typosquatted dependencies, autorun hooks, and fake-star signals before following or running them.

MCP server that provides npm package information for AI agents during TypeScript development.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

Enables coding agents to deterministically audit test files for fake or fragile tests (no assertions, tautological or swallowed assertions, focused/skipped tests, fixed sleeps, real network calls) and to run the project's actual test runner, treating an exit-0 run with zero tests as a failure and flagging changed source files that lack test coverage.

Enables source-first orchestration and knowledge indexing with inspectable architectural capabilities through a unified MCP interface, including named-attribute retrieval and atomic knowledge ingestion.

Serves local architectural context to LLM coding agents over MCP, enabling agents to query complexity, coupling, and layer metrics while deterministic quality gates enforce project invariants through hooks.

Enables security auditing of MCP servers by running them in a sandbox with fake secrets, capturing outbound traffic, and detecting tool poisoning or secret exfiltration before approval.

Enables AI coding agents to inspect Runable projects over MCP, providing read-only access to project information and configuration via Runable's inspector.

The server facilitates access to Julia documentation and source code through Claude Desktop, allowing users to retrieve information on Julia packages, modules, types, functions, and methods.

An MCP server for EndstoneMC development, enabling module information queries, code search, plugin template generation, event handling guidance, and development tutorials through natural language.

Enables agents to query information about gems in a Ruby project's Gemfile, including source code and metadata.

Enables AI assistants to audit, migrate, scaffold, and manage TON smart contracts using the TON Dev Skills platform.

Enables automated analysis of test suite traces to identify timing races and state pollution, helping developers mitigate flaky tests through MCP-compliant clients.

Enables AI coding agents and MCP clients to pull real-time language-server data from a running editor instance, including diagnostics, hover/definition/signature and type information, and symbol references with usage context. It also supports workspace-wide symbol renaming, opening files, and command execution, letting agents validate changes without waiting on slow tsc/eslint runs.

Enables MCP clients to extract GitHub repository information, including repository summaries, project directory structures, and file contents.

Enables MCP clients to quickly extract GitHub repository information, including summaries, project directory structures, and file contents.

Enables users and AI tools to query synchronized AOSP and AndroidX source code on demand for precise inspection of Android framework internals and Jetpack libraries. Supports class and method lookup, class member listing, inheritance hierarchy, source search, and optional cross-file definition, reference, and type information via LSP.

Enables analyzing Nix flakes to identify which inputs are actually used and to detect locked-input drift, including unportable or orphaned inputs, through MCP tools.

Enables on-demand, precise access to AOSP and AndroidX source code, allowing AI tools to inspect framework internals, search classes and methods, trace inheritance and references, and retrieve type information from a locally synced cache.

Enables AI assistants to search and read real AOSP and AndroidX source code on demand, including class lookups, precise method bodies with Javadoc, inheritance hierarchies, regex source search, and optional LSP-powered cross-file definition, reference, and type information. Sources are synced locally so framework internals like the Activity lifecycle, ViewModel restoration, or Compose internals can be inspected offline without relying on outdated training data.