Kortx MCP Server
Provides access to OpenAI GPT-5 models for planning, alternatives, copy improvement, debugging, expert consultation, and image generation.
Provides real-time research with citation-backed answers and image search through Perplexity Sonar models.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Kortx MCP Server research the latest GPT-5 features"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Kortx
Quick Start • Documentation • Examples • Contributing
Kortx is a lightweight Model Context Protocol (MCP) server that gives coding copilots access to:
OpenAI GPT-5 models (
gpt-5,gpt-5-mini,gpt-5-nano,gpt-5-codex,gpt-5.1-2025-11-13,gpt-5.1-codex) with automatic fallback.Perplexity Sonar models for real-time research.
GPT Image (
gpt-image-1) for visual generation and editing.A default context gatherer that can ingest local file excerpts and optional connectors for Serena, MCP Knowledge Graph, and CCLSP MCP servers when those are running.
The server ships with structured logging, request rate limiting, response caching, and a hardened Docker build that runs as a non-root user. Transport is stdio-only today (HTTP is not implemented yet).
Highlights
Seven consultation tools plus a batch runner covering planning, alternatives, copy improvement, debugging, expert consultation, research, and image workflows.
File-based context enrichment out of the box, with pluggable MCP connectors ready for Serena/MCP Knowledge Graph/CCLSP when available.
Perplexity integration (requires API key) for citation-backed answers and image search.
Configurable OpenAI model, reasoning effort, verbosity, and retry behaviour.
Built-in rate limiting, cache, and optional audit logging to avoid flooding upstream APIs.
Dockerfile uses multi-stage build, npm audits, and runs as UID/GID 1001.
Related MCP server: MCP Plus
Quick Start
Set credentials (both keys are required by the current config):
export OPENAI_API_KEY=sk-your-openai-key export PERPLEXITY_API_KEY=pplx-your-perplexity-keyAdd Kortx to your MCP client. Example generic configuration:
{ "mcpServers": { "kortx-mcp": { "command": "npx", "args": ["-y", "@effatico/kortx-mcp@latest"], "env": { "OPENAI_API_KEY": "${OPENAI_API_KEY}", "PERPLEXITY_API_KEY": "${PERPLEXITY_API_KEY}" } } } }
Client-specific walkthroughs for Claude Code, VS Code Copilot, Cursor, and others are available under docs/integration.
Tool Overview
think-about-plan– Structured review of plans with strengths, risks, and follow-up questions.suggest-alternative– Generates viable alternatives with trade-offs and constraints.improve-copy– Refines technical copy with tone, clarity, and accessibility guidance.solve-problem– Debugging assistant covering root cause analysis and remediation steps.consult– Expert consultation with domain-specific personas (software-architecture, security, performance, database, devops, frontend, backend, ai-ml, general).search-content– Perplexity-backed web/academic/SEC search with citations and optional images.create-visual– GPT Image based generator/editor; search mode reuses Perplexity for visual inspiration.batch-consult– Runs multiple tool calls in parallel and returns aggregated results.
Every consultation tool accepts an optional preferredModel. The OpenAI client falls back through gpt-5.1-2025-11-13 → gpt-5.1-codex → gpt-5 → gpt-5-mini → gpt-5-nano automatically on failures.
Configuration Essentials
Minimum environment variables:
OPENAI_API_KEY– requiredPERPLEXITY_API_KEY– required (disable Perplexity integration by omitting thesearch-content/create-visualsearch mode if you do not have a key)
Common overrides (see .env.example for the full list):
# OpenAI behaviour
OPENAI_MODEL=gpt-5-mini # gpt-5 | gpt-5-mini | gpt-5-nano | gpt-5-codex | gpt-5.1-2025-11-13 | gpt-5.1-codex
OPENAI_REASONING_EFFORT=minimal
OPENAI_VERBOSITY=low
OPENAI_MAX_TOKENS=1024
# Safety & performance
ENABLE_RESPONSE_CACHE=true
CACHE_MAX_SIZE_MB=100
ENABLE_RATE_LIMITING=true
MAX_REQUESTS_PER_HOUR=100
# Context gathering
ENABLE_SERENA=false # flip to true when a Serena MCP server is reachable
ENABLE_MEMORY=false # same for MCP Knowledge Graph
ENABLE_CCLSP=false # same for cclsp
INCLUDE_FILE_CONTENT=trueNote The Serena, MCP Knowledge Graph, and CCLSP connectors are stubs that return data only when the corresponding MCP servers are running and reachable. Out of the box the gatherer uses on-disk file excerpts referenced in prompts.
Full reference: docs/configuration.md
Docker
Build and run locally:
docker build -t kortx-mcp .
docker run -i --rm \
-e OPENAI_API_KEY=$OPENAI_API_KEY \
-e PERPLEXITY_API_KEY=$PERPLEXITY_API_KEY \
kortx-mcpThe image:
Uses Node.js 22 Alpine
Performs
npm auditduring buildCopies only the compiled
build/artefacts and production depsRuns as user
nodejs(UID 1001)
Compose example (docker-compose.yml) is included for longer-lived runs with volume mounts.
Development
git clone https://github.com/effatico/kortx-mcp.git
cd kortx-mcp
npm install
cp .env.example .env
npm run build
npm run devUseful scripts:
npm test/npm run test:coveragenpm run lint/npm run lint:fixnpm run format/npm run format:checknpm run inspector– launch MCP Inspector for interactive debugging
Node.js ≥ 22.12.0 and npm ≥ 9 are required.
Documentation
Contributing & Support
License
MIT © Effati Consulting AB. See LICENSE.
Available Tools
8 toolsbatch-consultA
Execute multiple consultation requests in parallel. Accepts an array of tool calls and executes them concurrently for improved performance.
Inputs: requests (required).
consultB
Ask domain-specific questions with expert consultation. Supports multiple domains: software-architecture, security, performance, database, devops, frontend, backend, ai-ml, or general.
Inputs: question (required), domain, context, constraints, +1 more.
create-visualA
Create, edit, or search for visual content. Supports three modes: generate (create images from text), edit (modify existing images), and search (find visual inspiration from the web). Note: Supported image sizes are 1024x1024, 1536x1024, 1024x1536, or auto - custom sizes like 512x512 are not available.
Inputs: mode (required), prompt (required), model, size, +11 more.
improve-copyB
Improve text, documentation, or messaging. Focuses on clarity, conciseness, tone, structure, technical accuracy, and accessibility.
Inputs: originalText (required), purpose (required), targetAudience, preferredModel.
search-contentA
Perform real-time web search using Perplexity Sonar models. Returns comprehensive, well-sourced answers with citations from the web.
Inputs: query (required), model, searchMode, searchRecencyFilter, +4 more.
solve-problemC
Debug and problem-solving assistance. Performs root cause analysis, provides diagnosis steps, solutions, testing guidance, and prevention strategies.
Inputs: problem (required), attemptedSolutions, errorMessages, relevantCode, +1 more.
suggest-alternativeB
Suggest alternative approaches or solutions. Considers different paradigms, simpler solutions, proven patterns, and trade-offs.
Inputs: currentApproach (required), constraints, goals, preferredModel.
think-about-planB
Get strategic feedback on plans and approaches. Analyzes clarity, feasibility, risks, dependencies, and suggests alternatives.
Inputs: plan (required), context, preferredModel.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 8 tools
Each tool has a distinct purpose: parallel consultation, single consultation, image operations, text improvement, web search, debugging, alternatives, and planning. No overlapping functionality.
All tool names follow a consistent hyphenated lower-case verb-noun pattern (e.g., create-visual, search-content), with 'consult' as a simple verb fitting the pattern. No mixed conventions.
With 8 tools, the server covers a broad range of consultation services without being excessive. Each tool adds clear value, and the count is appropriate for a general-purpose expert assistant.
The tool set covers key consultation needs: asking questions, searching the web, planning, problem-solving, improving copy, and creating visuals. No obvious gaps for a general assistant; all core workflows are supported.
Maintenance
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