MCP Tool Chainer
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
image
Step function like JSON paths:
image
Features
- Chain multiple MCP tools together in sequence
- Pass results from one tool as input to another tool using
CHAIN_RESULTplaceholder
- Filter and extract specific data using JsonPath with
inputPathandoutputPathparameters
- Automatic tool discovery from configured MCP servers
- Minimal token usage compared to individual tool calls
Tools
This server implements the following MCP tools:
mcp_chain- Chain together multiple MCP servers
chainable_tools- Discover tools from all MCP servers so the mcp_chain tool can be used
discover_tools- Rediscover tools from all MCP servers
Installation
Prerequisites
- Node.js (v16 or later)
- npm
Installing from npm
Installing from source
Usage with Claude Desktop, Cursor etc
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:If installed from npm globally
If installed from source
Replace
/path/to/mcp-tool-chainer with the actual path to your repository.image
Examples
Chain Browser and XPath Tools
Using JsonPath with InputPath and OutputPath
JsonPath Support
MCP Tool Chainer now supports AWS Step Functions-style InputPath and OutputPath features:
- inputPath: JsonPath expression to extract specific portions of the input before passing to a tool
- outputPath: JsonPath expression to extract specific portions of the output before passing to the next tool
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.
Benefits
- Reduced Token Usage: By chaining tools together, you avoid sending large intermediate results back to the LLM
- Simplified Workflows: Create complex data processing pipelines with a single tool call
- Improved Performance: Reduce latency by minimizing round-trips between the LLM and tools
- Precise Data Flow Control: Extract only the data you need with JsonPath expressions
Development
License
This MCP server is licensed under the MIT License.
Created by Third Strand Studio
MCP Tool Chainer
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
image
Step function like JSON paths:
image
Features
- Chain multiple MCP tools together in sequence
- Pass results from one tool as input to another tool using
CHAIN_RESULTplaceholder
- Filter and extract specific data using JsonPath with
inputPathandoutputPathparameters
- Automatic tool discovery from configured MCP servers
- Minimal token usage compared to individual tool calls
Tools
This server implements the following MCP tools:
mcp_chain- Chain together multiple MCP servers
chainable_tools- Discover tools from all MCP servers so the mcp_chain tool can be used
discover_tools- Rediscover tools from all MCP servers
Installation
Prerequisites
- Node.js (v16 or later)
- npm
Installing from npm
Installing from source
Usage with Claude Desktop, Cursor etc
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:If installed from npm globally
If installed from source
Replace
/path/to/mcp-tool-chainer with the actual path to your repository.image
Examples
Chain Browser and XPath Tools
Using JsonPath with InputPath and OutputPath
JsonPath Support
MCP Tool Chainer now supports AWS Step Functions-style InputPath and OutputPath features:
- inputPath: JsonPath expression to extract specific portions of the input before passing to a tool
- outputPath: JsonPath expression to extract specific portions of the output before passing to the next tool
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.
Benefits
- Reduced Token Usage: By chaining tools together, you avoid sending large intermediate results back to the LLM
- Simplified Workflows: Create complex data processing pipelines with a single tool call
- Improved Performance: Reduce latency by minimizing round-trips between the LLM and tools
- Precise Data Flow Control: Extract only the data you need with JsonPath expressions
Development
License
This MCP server is licensed under the MIT License.
Created by Third Strand Studio