"TradingView - Stock Charts and Financial Analysis Platform" matching MCP servers:

A Model Context Protocol (MCP) server for interacting with MongoDB stock data to provide portfolio recommendations and market insights, exclusively for the Indian stock market (NSE/BSE).

Bridges Hermes Agent to the Hermes Intelligence Platform API, enabling tools to read/write learning loop data (context, feedback, signals, memory, etc.) via stdio.

A read-only MCP server for exploring and analyzing a Secoda data catalog, enabling AI chat, semantic search, glossary browsing, and data lineage tracing.

A lightweight MCP server for intelligent, non-invasive analysis of Obsidian vaults.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

MCP server for persistent project knowledge management, enabling AI assistants to store, search, and reuse project analysis insights with freshness checking and impact analysis.

MCP server that parses aviation accident reports (PDF/DOCX/TXT) and injects their content into extraction prompt templates for knowledge graph construction.

MCP server for integrating manufacturing systems (MES/ERP/quality/maintenance) with LLM agents, enabling event ingestion, incident triage, approval workflows, and RAG-based knowledge retrieval.

Connects AI assistants to your Argo campaigns via the Model Context Protocol. Once configured, your AI assistant can read and write campaign lore, look up character details, and interact with Argo data directly from the chat interface.

Facilitates semantic analysis of chat conversations through vector embeddings and knowledge graphs, offering tools for semantic search, concept extraction, and conversation pattern analysis.

提供文档智能问答的MCP服务器，支持查询知识库、获取会话历史和清理会话历史。

Owner-controlled continuity layer for Obsidian and AI agents, enabling cited handoffs and owner decisions across independent agents.

Enables AI assistants to retrieve, search, and compare procurement documents using hybrid retrieval and MCP integration.

Japan Operations OS for AI agents — 14 knowledge domains covering regulations, protocols, calendar, travel, food culture, language, disaster safety, daily life, and persistent memory. 31 MCP tools via REST + Streamable HTTP.

Enables AI agents to self-register, authenticate, and operate a no-code ontology and knowledge-graph platform for facility management, field service, CRM, fleet management, workflow automation, and related business processes through 172 tools.

Enables qualitative analysis through a strict TypeDB ontology that verifies evidence quotes and refuses method-breaking changes, while agents use MCP tools to add concepts, themes, dimensions, memos, and checkpoints. Supports append-only event logs for replay, forking, and comparison across staged analysis runs.

Transforms codebases into a living knowledge graph with AI-powered code analysis, security scanning, and persistent semantic memory, leveraging Oracle 26ai vector and property graph capabilities.

Enables AI assistants to access competitive-intelligence signals, reports, and memory through a tenant-scoped MCP endpoint with security controls.

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.