"Search results for 'Taisly'" matching MCP servers:

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.

An MCP server for executable mathematics that enables agents to construct objects, compute invariants, search for witnesses, and verify results with independently checkable evidence.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

Provides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.

Free Industry 4.0 / IIoT tools, no API key or account: lint MQTT Sparkplug B topics, check a Unified Namespace (UNS) for naming and hierarchy problems, and run an industrial AI-readiness diagnostic for manufacturing digital transformation and smart-factory projects. Works in Claude Code, Codex and any MCP client.

Local MCP server that manages a job search using Markdown files, enabling skills tracking, gap analysis, and offer pipeline management via Claude.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

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 shared context caching with trust verification -- AI agents share and verify computed results to reduce token cost and increase reliability.

Gives agents a stable interface for durable memory, combining exact, lexical, semantic, and graph search results.

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.

A system for defining, composing, and managing task-specific contexts for AI-powered development, enabling consistent, high-quality results.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

An MCP server for Claude Code that enables semantic search of past session transcripts and intelligent session forking, allowing users to find and resume from relevant previous conversations with full context.

Interacts with LogSeq via its API.

An MCP server that exposes unified tools for HTTP requests, web search and fetching, weather/time/currency, file and SQLite sandboxes, GitHub, email, calendars, and a self-learning SQLite FTS5 knowledge base. It supports stdio, SSE, and streamable-HTTP transports with Bearer-token auth and SSRF protection so AstrBot agents can call these capabilities directly.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

An intelligent, agentic MCP server gateway to OpenRouter's 200+ AI models. It provides budget controls, security features, semantic memory, and code search capabilities.

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 creation of new mathematical formulas through symbolic derivation, verification, and step-by-step control, leveraging SymPy for computation and storing results with provenance.

Enables agents to query a CompanyGraph instance read-only, retrieving types, schemas, entities, skill evidence, and search results with verbatim answers from a specific model commit.

Enables AI agents to store, search, list, and forget long-term memories in a fixed namespace backed by S3-compatible storage, with optional read-only mode and provenance-tagged recall results.

A knowledge graph MCP server providing persistent, structured memory for AI assistants with multi-agent isolation, tiered search, and index navigation.

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.

Enables AI agents to query and modify RDF data, list named graphs, and access pre-built SPARQL templates on a Fuseki server, with optional HTTP Basic authentication.

Enables Claude to search and analyze Obsidian vault content using ripgrep with support for wiki links, backlinks, frontmatter properties, orphaned notes, and intelligent context detection showing which heading or property contains each match.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Enables fully local semantic search over a Roam Research graph via MCP, providing tools for hybrid retrieval, index refresh, and stats while keeping all content on-machine.