Integrations
Allows creation and management of prompt templates from markdown files in the 'prompts' folder, with variable templating support using {{variable}} format
Provides web search results with summaries through perplexity.io as a tool for AI agents
Server implementation that exposes customizable prompt templates, resources, and tools for AI-assisted development
Model Context Protocol ( MCP ) Python server to use with continue.dev
MCP server that exposes a customizable prompt templates, resources, and tools It uses FastMCP to run as server application.
Dependencies, build, and run managed by uv tool.
Provided functionality
prompts
prompts created from markdown files in prompts
folder.
Additional content can be added by templating, by variable names in {{variable}} format
Initial list of prompts:
- review code created by another llm
- check code for readability, confirm with Clean Code rules
- Use a conversational LLM to hone in on an idea
- wrap out at the end of the brainstorm to save it as
spec.md
file - test driven development, to create tests from spec
- Draft a detailed, step-by-step blueprint for building project from spec
resources
NOTE: continue does not understand templates, so resource name should contain all information resouce name left as is in prompt, so it should not confuse llm
- extract url content as markdown
- full documentation about libraries, preferable from llms-full.txt
- complete project structure and content, created by
CodeWeawer
orRepomix
tools
- web search, using
serper
or - web search results with summary, by
perplexity.io
- find missed tests
- run unit tests and collect errors
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hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A Python server implementing the Model Context Protocol to provide customizable prompt templates, resources, and tools that enhance LLM interactions in the continue.dev environment.
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