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    Enables a model to write short Python programs that call a wrapped MCP server's tools as async functions, rather than invoking them one at a time. The program runs in a locked-down Docker sandbox, and every tool call passes through a host-side bridge that enforces an allowlist, schema-validated arguments, call budgets, timeouts and output caps.
    1
    MIT
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    An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.
    10
    69,997 npm
    2
    Elastic 2.0
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    Cross-platform MCP server providing Claude Code-style plan mode via four tools (enter_plan_mode, get_plan_mode_standards, todo_write, exit_plan_mode) with soft guidance through SKILL.md.
    5
    Apache 2.0
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    Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.
    11
    69,997 npm
    Elastic 2.0
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    An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.
    11
    69,997 npm
    33,979
    Elastic 2.0
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    Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.
    6
    Apache 2.0
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    Provides League of Legends mode-specific data including Arena augments, ARAM balance numbers, and mode mechanics, supporting both Chinese and English queries.
    4
    MIT
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    Enables MCP-compatible AI assistants and agents to browse reports, manage queries, and fetch results from Mode Analytics, with optional authoring/archiving and configurable read-only or delete controls.
    13
    MIT
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    Enables AI assistants to automate Microsoft Edge in IE mode through Selenium and IEDriver, letting them inspect legacy pages, fill forms, click controls, handle frames, alerts, windows, and file uploads.
    32
    MIT
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    Enables AI assistants to send real faxes through the FaxDrop API. Provides safeguards including rate limiting, dry-run mode, and audit logging for secure fax operations.
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    95 npm
    5
    MIT
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    Enables MCP clients like Claude Desktop and Claude Code to drive a real browser with SeleniumBase automation. Offers three variants: WebDriver-based general automation, Pure CDP Mode for bot-detection bypass, and a broad SB() API with MFA and downloads.
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    291 PyPI
    10
    MIT
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    MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.
    7
    107 PyPI
    50
    MIT
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    Enables AI agents to safely explore and query a SQLite database in read-only mode, allowing them to inspect schema and run analytical SQL queries without risking data modification.
    3
    MIT
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    Enables searching and downloading court documents, listing cases, and retrieving case details via the DocketBird API. It supports secure OAuth 2.0 authentication for remote access and a standard local mode for personal use.
    16
    Apache 2.0
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    Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.
    3
    MIT
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    An MCP server that gives text-only models image generation and understanding capabilities, with tools like generate_image, describe_image, and set_api_key. It enables any MCP client to create and analyze images using a single API key.
    4
    MIT
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    Enables AI agents to self-report bugs, ambiguities, and improvement requests via a single report_issue tool, logging to PostgreSQL or JSONL with severity and mode classification.
    1
    LGPL 3.0
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    Enables AI agents to intelligently organize Git changes into clean, focused commits with autopilot mode or surgical line-by-line staging precision. Supports partial staging of untracked files and handles large diffs with smart truncation.
    5
    MIT
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    An advanced integration package that leverages OpenRouter and Perplexity APIs to provide enhanced web search capabilities, offering both simple and complex query processing with file attachment support.
    1
    24 PyPI
    49
    MIT
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    Indexes codebases cut at function and class boundaries into Oracle AI Database 26ai, letting AI coding tools search code by name or meaning, trace callers, callees and change impact, read per-module wiki pages, and recall facts from earlier sessions. All of it is served over the Model Context Protocol with embeddings computed in-database, so no source code leaves the machine and no API key is required.
    9
    MIT
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    An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.
    6
    35 PyPI
    2
    MIT
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    Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.
    4
    Apache 2.0
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    🔌 Complete MCP server for Zabbix integration - Connect AI assistants to Zabbix monitoring with 40+ tools for hosts, items, triggers, templates, problems, and more. Features read-only mode and comprehensive API coverage.
    3
    262
    GPL 3.0