"A search query containing special characters and SQL injection-like encoding" matching MCP servers:

Enables Claude to write in your personal style by learning from your local documents. It provides statistical style context for natural language rewriting, all without any data leaving your machine.

Enables fast, targeted queries against an Obsidian vault knowledge graph using tools like search, neighbor traversal, and pathfinding, without needing to load the full graph into LLM context.

Automatically injects development framework context and workflows into Claude conversations, ensuring Claude follows your established patterns without manual context provision each time. Supports custom frameworks, keyword triggers, and Knowledge Graph integration.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Enables local, read-only keyword search across past Claude Code, Codex, Gemini CLI, and ChatGPT conversations plus markdown notes, with exact source citations and context retrieval.

Enables MCP clients to execute SELECT-only SQL against a music-store schema with statement timeouts, guardrails, and retry/reflection support.

Enables agents to store LLM query-response pairs and retrieve them via fuzzy cosine similarity matching, reducing duplicate inference calls; it exposes tools for setting cache entries, semantic lookup, and hit-rate statistics.

Enables semantic search across conversation archives via MCP, allowing AI clients to retrieve relevant past conversations using vector embeddings and text fallback.

A federation MCP server that sits in front of multiple memory backends and presents a unified search surface to AI agents, allowing a single query to search across knowledge graphs, session history, and web search.

An MCP server that transforms natural language questions into SQL, executes queries on PostgreSQL, and returns human-friendly responses, with Redis memory for context.

Full-text search over Claude Code conversation history using SQLite FTS5, exposing indexed transcripts as MCP tools for searching, browsing, and reading turns.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

An MCP server that provides safe access to your iMessage database through MCP, enabling LLMs to query and analyze iMessage conversations with proper phone number validation and attachment handling

Enables keyword search, filtering, and retrieval of Claude Code memory files, reducing context overhead by fetching only relevant memories on demand.

Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.

MCP server for Yandex Wiki with full-text search. Read and write pages, comments, attachments, and dynamic tables (grids); optional server-side read-only mode for agents. Docker-ready.

MCP bridge for PDF Content Search — full-text PDF search with Apple Vision OCR across thousands of documents in under a second from Claude, Cursor, or any MCP client. Advanced filters (date, category, sender, amount), wildcards, boolean operators. Bridge open-source (MIT), PDF Content Search app is commercial with free iOS+Android companion scanner apps.

Enables AI agents to search through Memex conversation history and local project files to retrieve specific commands, code snippets, and technology overviews. It utilizes smart context management and faceted filtering to provide relevant search results without causing context overload.

Persistent memory system for AI agents that records episodic memories with care-weighting and emotional valence, and provides full-text search with temporal chaining and automatic consolidation.