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"Understanding Abstract Syntax Trees (AST)" matching MCP servers:

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    Provides application insights for Vue apps by exposing component trees, state, routes, and Pinia data through a Model Context Protocol server.
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    MIT
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    An MCP server that decodes V8 CPU profiles into token-efficient bottleneck summaries for AI agents, enabling them to analyze CPU consumption, call trees, GC pressure, and async bottlenecks.
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    The MCP server for Nanostores that scans your codebase with AST analysis to find stores, subscribers, and dependency chains, and can ingest live events to spot noisy, error-prone, or unused stores.
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    Security, cost, and health governance proxy for MCP infrastructure. Enforces YAML-configurable security policies (blocklists, rate limits, token budgets), tracks real token costs via tiktoken, monitors server health with live JSON-RPC probes. Features OAuth 2.1/OIDC with RBAC, web dashboard, payload normalization, semantic shell AST analysis, mTLS, and a formal STRIDE threat model.
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    Integrates AI assistants with Graylog to query and analyze log data using Elasticsearch syntax and stream-specific filtering. It enables users to perform advanced searches, retrieve log statistics, and manage Graylog streams through natural language.
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    Connects AI assistants to ActivityWatch for real-time computer activity awareness and time tracking analysis. Enables natural language queries about app usage, browsing history, and productivity patterns through high-level tools without requiring AQL syntax knowledge.
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    Provides production insights and code analysis by leveraging Nexus instrumentation data to identify CPU-intensive methods and visualize execution flow trees. It enables developers to make data-driven decisions through real-time performance metrics and automated service discovery from Java class names.
    Last updated