"A platform for professional networking and job searching" matching MCP servers:

Enables agent-native collaboration network for long-running agents and MCP clients with shared context, tasks, and interactive MCP App widgets.

An AI-powered job search and application assistant that enables multi-source job hunting, OpenAI matching, cover letter generation, and hybrid application automation via Playwright, Chrome CDP, screen OCR, and manual assist.

Profile-driven job search engine that aggregates postings, scores them against a user's profile, filters by eligibility (location, timezone, work authorization), and exposes find_jobs, list_sources, and describe_engine to local AI agents over MCP.

Enables MCP clients to submit long-running jobs that are executed safely in isolated child processes with a durable SQLite queue, configurable timeouts, retries with backoff, and backpressure.

Score your agent's governance (0-100), lint MCP tool definitions, and estimate costs across all major models. Free diagnostic tools with no API key needed. Expert skill files on governance, economics, and system architecture available with free tier.

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.

An MCP server that exposes job-search and application-management capabilities to compatible AI clients, enabling discovery of vacancies, drafting of tailored application materials, and coordinated human-approved submissions.

A shared communication bus for multiple agents using NATS and MCP, enabling MCP clients to list, message, and query agents.

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.

This server enables remote job discovery, tailored CV creation, and approval-gated application lifecycle management. It prioritizes safe, factual job applications without authenticated LinkedIn scraping or silent submissions.

This MCP server enables job intelligence retrieval and ranking, providing tools to list jobs, fetch details, access corpus statistics, and score candidates against job descriptions using staged retrieval to optimize LLM context usage.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

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

An MCP server that enables AI agents to evaluate candidate-job fit by calculating weighted match scores based on skills and requirements.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

An AI-centric MCP server that enables automated Xilinx Vivado workflows, including project management, synthesis, implementation, and timing analysis. It allows AI agents to drive hardware design processes while integrating directly with the official Vivado GUI for visual context.

MCP server for the Sayba AI agent social platform, enabling agents to register, browse, interact, manage goals, trade skills, and exchange items via natural language.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

A local MCP server that lets Hermes supervise Claude Code, delegating focused coding, research, or review tasks to the Claude Code CLI and managing worker sessions, background jobs, cancellations, and read-only reviews.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.