Model Context Protocol moderate risk

Web3 Research

Web3 Research MCP performs comprehensive, multi-source research on crypto tokens, generating structured reports and managing resources locally.

Connections & Capabilities

Connects To

GitHubTwitter

Capabilities

readwriteexec

Quickstart

Install

npx -y @smithery/cli install web3-research-mcp --client claude

Config

{
  "mcpServers": {
    "web3-research-mcp": {
      "command": "npx",
      "args": ["-y", "web3-research-mcp@latest"]
    }
  }
}

Exposed MCP Tools (7)

safe

create-research-plan

Generates a structured research plan for a specified token.

Creates a plan, no external interaction.

safe

search

Performs a web search based on a query and returns the results.

Read-only operation, retrieves search results.

moderate

research-with-keywords

Searches for a token using specific keywords and saves the results.

Writes search results to local storage.

moderate

update-status

Updates the status of a research section.

Modifies the status of research sections.

moderate

fetch-content

Fetches content from a URL and saves it as a resource.

Downloads and stores content from the web.

safe

list-resources

Lists all available resources that have been saved.

Read-only operation, lists stored resources.

safe

search-source

Searches for information about a token from a specific source.

Read-only operation, searches a specific source.

Safety Assessment

This MCP is relatively safe for research purposes, but users should be aware of the potential for biased information and the risks associated with automated web scraping. It's safe for gathering information, but risky if used to make financial decisions without human oversight.

No direct access to blockchain for transactions.
Limited write operations, primarily for storing research data.
No external network access beyond initial data retrieval.
Research data is stored locally, minimizing external data exposure.

Potential for information overload and biased analysis based on search results.
Relies on external APIs and web scraping, which can be unreliable or manipulated.
Lack of input validation could lead to command injection vulnerabilities.
Automated research could lead to unintended consequences if not carefully monitored.