Enables AI agents to read the local, already-logged-in WeChat account's chat history: fetch recent messages per contact for reply suggestions, bulk-export all conversations into a local SQLite index for full-text and semantic search, and export media or Moments timelines as offline HTML. Everything runs locally and read-only on macOS, exposing 15 MCP tools plus a matching CLI.

Enables querying a city road graph for shortest routes by total distance and a 25-room maze for fewest-door paths, returning step-by-step trace explanations and animating each search in a live web viewer.

Enables any agent to search skill packs with bounded results, fetch one full validated skill on demand, and act without copying directories into prompts.

Enables MCP clients to search, classify, cite, and read EndNote X9 libraries locally, with PDF text extraction and narrowly scoped, backup-first field updates.

Enables MCP clients to inspect PDF structure and extract object-level data such as characters, words, tables, images, fonts, and metadata, with JSON/CSV export and image retrieval.

Enables any MCP-compatible client to persist long-term memories for AI agents, with LLM-based fact extraction, semantic vector search, update/delete/list operations, and queue status checks across sessions.

Enables MCP-compatible AI clients to search and view CRM customers, deals, contracts, tasks, calendars, and outbound jobs, and to propose opt-in write actions that require human approval in the CRM.

Gives AI agents a durable, locally hosted temporal memory built from a markdown vault you own, exposing hybrid semantic/lexical/entity search over events, threads, transcripts, entity relationships with validity dates, and patterns with confidence decay. Writes are approval-gated, so agents can draft, commit, and sync new memories while keeping every index rebuildable and nothing leaving your machine.

Enables offline King James Version Bible lookup, passage retrieval, word and phrase search, deterministic verse-of-the-day access, and book/chapter listing for AI assistants. All tools are read-only and return citable references with structured JSON.

Enables Claude to plan search-and-rescue operations on CalTopo maps by measuring terrain, staging areas, hasty search lines, parking, helicopter landing zones, egress routes, walking-time rings, hospitals, and urban assignments, and by exporting results as GeoJSON draft assignments. It is read-only and returns facts for human decision-making.

Enables AI agents to query a Python codebase as a knowledge graph over MCP, exposing symbol search plus callers, callees, and module dependency tools.

Enables MCP clients such as Claude to search, tag, catalogue, ingest, audit, relocate, and repair a running Connecter asset library, including texture scanning and relinking, with dry-run plans and undoable journaled changes.

Enables AI assistants to browse, search, read, and save personal Markdown knowledge through HTTP MCP tools, with category and status filtering, revision-safe updates, and rebuildable full-text search.

Enables querying aggregated security news and vulnerability feeds from Claude, with semantic search and filtering by severity, source, or category, plus real-time threat summaries.

Enables read-only access to generated technical documentation across one or multiple documented repositories, exposing tools to search code and docs, inspect modules and symbols, list gaps, review architecture, and check freshness with file#line citations.

Enables an AI assistant to search open roles at a configured short list of companies through official public Greenhouse, Lever, and Ashby job board APIs, filter matches by career lane, retrieve full job descriptions, and save selected roles to a Notion tracker.

Enables authorized AI clients to search locally stored WeChat conversations, media, and attachments, retrieve original-message context, and cite evidence through a local stdio MCP interface.

Enables MCP clients to search job listings, read complete job descriptions, manage local search presets and candidate pools, and prepare application or message drafts. Optional session-backed chat reading and human-confirmed single-action execution are also supported.

Enables MCP clients to perform speculative tree-search action prediction and prefetching using Laplace-smoothed Markov transitions, returning deterministic JSON tool results.

Enables agents to use ACT-R spreading activation memory, semantic association graphs, and automated memory consolidation via the Model Context Protocol.

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 agents to run multi-engine web searches, find GitHub repositories, and fetch web pages as Markdown with headless-browser fallback and automatic system-proxy support.

Enables discovery of official DHS country, survey, and indicator metadata; retrieval of public aggregate estimates; assessment of comparison risks; and export of auditable CSV, JSON, Excel, or executable notebook bundles.

Enables AI agents to search and invoke 1,939 Atlassian automation tools across Jira, Confluence, Bitbucket, Admin, Assets, and more, with cached reads and JSON-RPC over stdio. It helps agents find tools without calling Atlassian and execute operations while reducing rate-limit pressure.