Summary This repository offers an MCP server that integrates Open Strategy Partners' (OSP) proprietary methodologies into LLM workflows for technical content creation, optimization, and product positioning. It empowers technical writers, marketers, and product managers to generate high-quality, standardized content and enhance SEO.

How It Works The project functions as a Model Context Protocol (MCP) server, enabling MCP-compatible LLM clients (e.g., Claude desktop, Cursor IDE, LibreChat) to access OSP's advanced frameworks. It directly applies OSP's proven techniques for value mapping, metadata generation, content editing, technical writing, and on-page SEO within LLM interactions.

Quick Start & Requirements

• Installation: Requires Python 3.10+ and the uv package manager. An MCP-enabled LLM client (e.g., Claude desktop) must be installed separately.
• Configuration: Add specific entries to claude_desktop_config.json to register the osp_marketing_tools MCP server, pointing to its GitHub repository.
• Prerequisites: Python 3.10+, uv package manager, MCP-compatible LLM client.
• Links: OSP Writing and Editing Guide, Editing Codes Quickstart Guide, OSP Free Resources.

Highlighted Details

• OSP Product Value Map Generator: Automates creation of value maps, taglines, position statements, personas, and feature organization.
• OSP Meta Information Generator: Optimizes article titles, meta titles/descriptions, URL slugs, and suggests CTR enhancements.
• OSP Content Editing Codes: Applies semantic codes for comprehensive content review, covering scope, flow, style, technical accuracy, and inclusive language.
• OSP Technical Writing Guide & On-Page SEO Guide: Provides systematic frameworks for technical documentation and web content optimization, including structure, SEO, schema markup, and performance metrics.

Maintenance & Community Contributions are accepted via repository issues and pull requests. Support is available through documentation, repository issues, or direct contact with Open Strategy Partners for consulting services. No dedicated community channels (e.g., Discord, Slack) are listed.

Licensing & Compatibility Licensed under Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0). This license permits sharing and adaptation, including commercial use, provided attribution is given and derivative works are licensed under the same terms.

Limitations & Caveats Adoption is contingent on using an MCP-compatible LLM client, which may be a barrier for some users. The README does not specify performance benchmarks or detailed resource requirements beyond standard Python/LLM client needs.