"Help with Docker and Viewing Docker Logs" matching MCP servers:

Enables LLMs to explore and analyze UK Government BEIS inspect_ai evaluation logs directly from tools like Claude Code and Cursor. It provides capabilities to list logs, view evaluation summaries, and inspect conversation histories for specific samples.

Provides AI coding assistants with local access to 4500+ MQL5 documentation files and supplementary ebooks via MCP, enabling efficient search, browsing, and error diagnosis for MQL5 development.

Exposes Ghidra headless binary analysis capabilities via the Model Context Protocol, enabling AI assistants to decompile, analyze, and emulate binaries with 32 tools and multi-binary support.

Integrates local language models (like Qwen3-8B) with MCP clients, providing tools for chat, code analysis, text generation, translation, and content summarization using your own hardware.

Enables structured, iterative reasoning for complex problem-solving with features like confidence tracking, revision mechanisms, and branching support. Provides flexible validation and multiple output formats for systematic analysis and decision-making tasks.

locidx

Enables ChatGPT Pro web to securely read workspace files, git diffs, and test records through OAuth-protected read-only MCP tools, so it can plan and review while Codex handles execution without uploading the repository.

Enables interactive GitHub pull-request review from Claude Code, with tools to fetch PRs, inspect files and repo structure, post review comments, and query a RAG index of the codebase.

Provides code generation and completion capabilities using the DeepSeek API, with support for tool chaining and cost optimization.

A calibrated faithfulness screen for informal↔Lean 4 statement pairs, served over MCP. It provides deterministic checks and deep LLM-based analysis to help draft Lean statements.

AgentAvow scans any MCP server, package (npm/PyPI/crates/Docker/Hugging Face), or GitHub repo and returns a signed, offline-recomputable 0–100 trust score with a plain safe / needs-review verdict. Authless and read-only, no account.

High-performance local MCP server and CLI written in Rust that scrubs 90%+ framework noise from AI debug logs with Tree-sitter AST validation and test rollback.

Enables coding agents to identify likely runtime failures in JavaScript and TypeScript by ranking risky files, tracing dependencies, analyzing logs, and obtaining independent model reviews with line-level reasons.

Navigate, search, and edit large codebases, logs, and data files that exceed AI context limits.

Enables AI assistants to perform read-only introspection of Symfony applications, exposing routes, controllers, services, entities, database schema, migrations, logs, and more via MCP tools.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

Provides comprehensive Pine Script v6 documentation and tools to help AI assistants look up functions, validate syntax, and generate accurate code. It enables linting, version conversion from v5 to v6, and deep conceptual analysis to prevent code hallucinations.

Provides software design guidance via MCP, including SOLID principles, design patterns, pattern scaffolding, and heuristic code-smell detection to help review and refactor code.

A local-first MCP preflight system to help AI inspect Python repositories before generating code, enabling reuse, extend, or create decisions. Currently in early development with only foundational modules implemented.

Enables AI coding agents to reduce token usage by condensing source code into AST skeletons, extracting specific symbols, compressing logs, and estimating token budgets.