TSUNG AI Research & Analysis

io.github.a0985344368-glitchPublished by GitHub account a0985344368-glitchv1.0.0Updated Oct 24, 2026

Multi-LLM AI Research & Analysis — smart routing, consensus analysis, due diligence reports

VerifiedStreamable HTTPWeb executableAI & ML

Overview

AI-generated overview

A remote MCP endpoint that gives an assistant multi-LLM research and analysis, including smart routing, consensus analysis and due diligence reports.

What you can do
It exposes a hosted research and analysis service that draws on multiple LLMs. According to its description, it offers smart routing between models, consensus analysis across them, and due diligence reports. No individual tools are listed in the manifest, so the exact operations are not documented here.
When to use it
Consider it when you want an assistant to run research or analysis tasks that benefit from combining several LLM outputs, such as cross-checked consensus answers or due diligence write-ups. It is less suitable if you need a documented, granular tool list before adopting.
Requirements
A remote streamable HTTP endpoint; no local package or runtime is needed. Authentication is required: a bearer token sent in the Authorization header.
Before you install
You must supply a bearer token in the Authorization header; treat it as a secret and check how it is stored and shared. The service sends your prompts and data to a third-party hosted endpoint and to multiple LLM providers, so avoid confidential material unless that is acceptable. Report generation may consume paid model usage.

Installation

In SourceWeft

  1. Open TSUNG AI Research & Analysis in the dashboard and add it to a workspace.
  2. Connect Authorization token credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.a0985344368-glitch%2Ftsung-ai/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "tsung-ai-research-analysis": {
      "type": "http",
      "url": "https://tsung-mcp-custom.a0985344368.workers.dev/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

README

This repository has no README.

Tools

0
This server asks for a credential such as an API key, so SourceWeft could not read its tools without one and has not indexed them.

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

60% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts

    Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.

  • License10 pts

    Declare a license in the repository or the registry entry.