"How to execute trading operations on KuCoin" matching MCP servers:

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

Enables AI agents to discover and call existing OpenAPI services through governed tools, enforcing policy, approval for destructive operations, and credential handling before requests execute.

Enables AI agents to securely interact with FHIR R4-based EMRs, supporting read, search, create, and update operations on any FHIR resource type across systems like Epic, Cerner, and OpenEMR.

Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.

Enables governed multi-agent software factory operations through eight typed, audited tools for Sprint planning, submission, decisions, inspection, cancellation, and resumption.

Enables interaction with Trello boards, lists, and cards through MCP-compatible clients, allowing read and update operations on allowlisted boards.

Records how any command-line tool behaves (flags, stdin, outputs, exit codes, edge cases) as golden tests, then diffs a Rust or Go rewrite against the original to prove it behaves the same.

Enables AI agents to securely execute terminal commands with persistent sessions, async jobs, and mission control, while providing a live dashboard for human oversight.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

Enables AI agents to remotely execute shell commands and transfer files on SSH hosts, including jump-host tunneling, background tasks, resumable transfers, and optional approval of destructive commands, while SSH credentials remain in the local process. It runs over stdio or a streamable HTTP daemon and supports auditing, allow/deny lists, and multiple authentication methods.

Enables AI agents to interact with Kalshi event contracts and perpetual markets via a safety-focused MCP interface, with paper trading by default, strict schemas, and fail-closed behavior.

Allows external tools (VSCode, Claude Code, etc.) to access log output and errors, execute commands asynchronously, and monitor process status.

Enables LLMs to access banking, investment, and cryptocurrency data through a standardized MCP interface, featuring Plaid integration for account and transaction data and Robinhood for crypto trading with audit trails.

Manages skills and profiles on disk and probes companion tools (bob, cortex, mcphub, etc.) over stdio MCP, enabling library operations and stack readiness checks.

Enables signed-in users and organizations to discover and execute read or owner-confirmed write operations for monitoring sites, TLS certificates, traffic, suspicious requests, HTTP errors, Docker/Podman workloads, storage, data services, jobs, and node health. It connects through OAuth authorization code with PKCE and supports incident and TLS review prompts.

Records your terminal sessions per command (PTY + OSC 133) into local SQLite, so AI agents can search, retrieve, and diff what commands actually printed. Secret redaction is applied by default to everything served over MCP.

Model Context Protocol server for the NetLoc8 IP geolocation API. Gives AI assistants access to country/city lookup, timezone reconciliation, and IP utilities.

PCI DSS v4.0.1 compliance scanner for Go payment services, delivered as an MCP server. Every finding maps to a specific PCI DSS requirement ID. Taint-aware cardholder data flow analysis with PCI SSC FAQ semantics, designed to complement broad SAST tools like Semgrep and CodeQL - not replace them.

Turn any OpenAPI/Swagger/Postman spec into an MCP server — give your LLM live access to any API.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.