by thirdstrandstudio
Tool Chainer connects multiple MCP tools, streamlining complex workflows efficiently with reduced token usage.
Chains multiple MCP tools together in sequence, passing results between them without sending large intermediate data back to the LLM to reduce token usage.
Tool Chainer is a community-built MCP server published by thirdstrandstudio that provides AI assistants with tools and capabilities via the Model Context Protocol. Tool Chainer connects multiple MCP tools, streamlining complex workflows efficiently with reduced token usage. It is categorized under productivity, developer tools.
You can install Tool Chainer in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Tool Chainer is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We evaluated Tool Chainer against two servers with overlapping tools; this profile had the clearer scope statement.
Tool Chainer is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Tool Chainer reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Tool Chainer is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
I recommend Tool Chainer for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Useful MCP listing: Tool Chainer is the kind of server we cite when onboarding engineers to host + tool permissions.
We evaluated Tool Chainer against two servers with overlapping tools; this profile had the clearer scope statement.
Tool Chainer reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We evaluated Tool Chainer against two servers with overlapping tools; this profile had the clearer scope statement.
According to our notes, Tool Chainer benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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An MCP (Model Context Protocol) server that chains calls to other MCP tools, reducing token usage by allowing sequential tool execution with result passing. Designed to solve https://github.com/modelcontextprotocol/specification/issues/215
Step function like JSON paths:
CHAIN_RESULT placeholderinputPath and outputPath parametersThis server implements the following MCP tools:
mcp_chain - Chain together multiple MCP serverschainable_tools - Discover tools from all MCP servers so the mcp_chain tool can be useddiscover_tools - Rediscover tools from all MCP servers# Install
npm install @thirdstrandstudio/mcp-tool-chainer
# Or use with npx directly
npx -y @thirdstrandstudio/mcp-tool-chainer
# Clone the repository
git clone https://github.com/thirdstrandstudio/mcp-tool-chainer.git
cd mcp-tool-chainer
# Install dependencies
npm install
# Build the package
npm run build
ENSURE IT IS THE LAST MCP TO RUN OTHERWISE IT WILL HAVE TO RUN DISCOVERY AGAIN
Add the following to your claude_desktop_config.json or mcp.json:
{
"mcpServers": {
"mcp_tool_chainer": {
"command": "npx",
"args": ["-y", "@thirdstrandstudio/mcp-tool-chainer", "`claude_desktop_config.json` or `mcp.json`"],
"env": {}
}
}
}
{
"mcpServers": {
"mcp_tool_chainer": {
"command": "node",
"args": ["/path/to/mcp-tool-chainer/dist/index.js", "`claude_desktop_config.json` or `mcp.json`"],
"env": {}
}
}
}
Replace /path/to/mcp-tool-chainer with the actual path to your repository.
// Fetch a webpage and then extract specific content with XPath
const result = await callTool("mcp_chain", {
"mcpPath": [
{
"toolName": "mcp_browser_mcp_fetch_url",
"toolArgs": "{"url": "https://example.com"}"
},
{
"toolName": "mcp_xpath_xpath",
"toolArgs": "{"xml": CHAIN_RESULT, "query": "//h1"}"
}
]
});
// Fetch a webpage, extract specific content with XPath, then extract part of the result
const result = await callTool("mcp_chain", {
"mcpPath": [
{
"toolName": "mcp_fetch_fetch",
"toolArgs": "{"url": "https://api.example.com/data"}"
},
{
"toolName": "web_search",
"toolArgs": "{"search_term": CHAIN_RESULT}",
"inputPath": "$.results[0].title", // Extract only the first result's title from previous output
"outputPath": "$.snippets[*].text" // Extract only the text snippets from the search results
},
{
"toolName": "another_tool",
"toolArgs": "{"content": CHAIN_RESULT}"
}
]
});
MCP Tool Chainer now supports AWS Step Functions-style InputPath and OutputPath features:
These features work only when the input/output is valid JSON. If JsonPath extraction fails, the original input/output is used.
For JsonPath syntax reference, see JsonPath Syntax.
# Install dependencies
npm install
# Start the server
node dist/index.js config.json
# List available tools
node dist/index.js config.json discover_tools
This MCP server is licensed under the MIT License.
Created by Third Strand Studio
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.