"Yahoo Finance MCP (Model Context Protocol) Server" matching MCP servers:

An event-driven MCP server that enables agents to share context streams, publish and subscribe to events, manage tasks, and follow protocols, keeping a fleet of agents mutually context-aware in real time.

Read-only MCP server for searching Yahoo! Shopping products through the Yahoo! Shopping Item Search API v3. It supports keyword and JAN-code search with price, stock, condition, shipping, sorting, category, brand, seller, image-size, and pagination filters.

IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real

A persistent memory system for Large Language Models (LLMs) that enables continuous learning and knowledge retention across sessions through the Model Context Protocol (MCP).

Provides live financial data for any LLM agent, including stock quotes, crypto prices, SEC filings, XBRL financials, FX rates, and macro indicators, through ten MCP tools.

Read-only MCP server for the ITIN finance network, providing a verified institution directory, editorial guides, FAQs, and state-level context for ITIN holders seeking loans and credit cards.

Trust infrastructure for the agent economy.

An MCP server that gives AI assistants read access to real brokerage accounts and market data, with 39 tools for prices, technical analysis, SEC filings, and macro indicators, while order execution requires human approval via a separate dashboard.

Enables AI coding agents to offload large file reads and boilerplate code generation to cheaper or local worker models through MCP, reducing token consumption and keeping context clean.

AIFeed Open Standard. AIFeed Protocol to the building tools section. AIFeed enables web publishers to provide verified, token-efficient content feeds for AI agents.

Provides time intelligence, persistent memory and complete traceability for AI coding agents. Enables sophisticated activity tracking, timezone management, smart reminders, and cross-session continuity with support for both per-project and centralized storage modes.

Provides AI agents with deterministic, offline finance tools for commodity margin analysis, loan covenant compliance, invoice auditing, AP exception classification, and five-day close readiness.

Enables AI assistants to retrieve live BIST and global stock prices, cryptocurrency prices, exchange rates, currency conversion, and inflation data from free public sources without API keys.

Open-source MCP server for Autodesk Revit 2022 to 2027: read, audit and edit live models with 89 tools, one Undo entry per change, and a workstation read-only lock.

Gaia Protocol—a planetary DAO for global resource management using quantum-entangled ledgers and algorithmic governance.

Enables users to search locally across imported Claude, ChatGPT, and Claude Code conversations and retrieve surrounding turns with citations, while keeping indexing and storage on their own computer.

Provides an external context buffer so a local model can maintain session memory across long tasks and search and page through large documents without loading them whole into its limited context window.

Lets MCP clients query financial news as structured, sourced statements and topics — searching by symbol, sector, theme, sentiment, importance and time range, and retrieving trending developments, topic detail, news-volume and sentiment series, and attention-screened symbols or sectors. It also exposes reference metadata such as the data window and known incidents.

Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.

Proxy for OpenAI-compatible backends that compacts conversation history before the context window fills, with read-only MCP tools to search and read back the archived originals.

Durable project-memory MCP: decisions, constraints, and pipelines across Claude sessions

Deterministic, local-first context optimization for AI coding agents. Automatically compresses raw development session data (messages, tool logs, error stack traces, and git diffs) into a compact, task-specific context window. Operates 100% locally with zero external LLM dependencies, ensuring your source code never leaves your machine.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

Enables writers to verify figures in Korean finance articles against official DART filings, Bank of Korea ECOS statistics, and US Treasury data, flagging reversed merger ratios, unit errors, and market-number mismatches.

Local-first memory for AI agents about the people in your life. MCP server + CLI on SQLite. Never phones home.

Sovereign, deterministic, local-first context and DAG lifecycle engine with native stdio MCP server for autonomous AI coding agents.

Invoicing, full accounting, year-end preparation and taxes for freelancers and small businesses in the EU, including Germany and Poland.

Enables bounded, local coding tasks to be delegated to OpenAI-compatible models with explicit working directory and read/write paths, pre-application unified-diff validation, and optional verification commands. It routes tasks by complexity and risk, while blocking sensitive changes such as auth, payment, secrets, migrations, database, deployment, or production environments.

Temporal knowledge graph for codebases that captures decision traces, links test failures to code changes, learns co-edit patterns, predicts regression risk, and enforces learned constraints at the edit boundary via a PreToolUse hook.

Read-only repository context explorer for coding agents. Provides repository exploration tools via CLI or MCP adapter.