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Volume Wall Detector

Volume Wall Detector MCP Server provides real-time analysis of stock trading data to identify significant price levels (volume walls) where substantial trading activity occurs. Built with TypeScript and MongoDB integration, it offers tools for fetching order book data, retrieving recent trades, and analyzing volume distribution across price points. The server calculates volume and value imbalances, tracks regular and after-hours trading patterns, and identifies key support/resistance levels based on accumulated trading activity. Particularly valuable for traders seeking to understand market structure, identify potential price reversal points, and analyze buying/selling pressure at different price levels.

Cognium trust score

89%

Tier

Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.

Scan details: Circle-IR · 2026-09-28 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: database
Source: PulseMCP
Repository: github.com/cognitive-stack/volume-wall-detector-mcp
Author type: human
Last scanned: 2026-09-28
Updated: 2026-09-28

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MCP

Resolve Volume Wall Detector from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"