Provider agnostic skills implementation, with skills sourced from local paths or GitHub repositories
MCPpedia last refreshed this data
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"tiger-skills": {
"env": {
"GITHUB_TOKEN": "ghp_whatever"
},
"args": [
"/absolute/path/to/tiger-skills-mcp-server/dist/index.js",
"stdio"
],
"command": "node"
}
}
}Are you the author?
Add this badge to your README to show your security score and help users find safe servers.
Emulate Claude Skills with any LLM via a Model Context Protocol (MCP) server.
No automated test available for this server. Check the GitHub README for setup instructions.
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
Be the first to review
Have you used this server?
Share your experience — it helps other developers decide.
Sign in to write a review.
Others in other
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
Pi Coding Agent extension (CLI-first) — routes bash/read/grep/find/ls through lean-ctx CLI for strong token savings. Optional MCP bridge can register advanced tools.
97% token reduction for AI coding sessions — zero deps, 21 languages, MCP server
One local source for the MCP servers, tools, and memory your AI coding agents share, synced into each tool's native config with a review gate and a receipt for every change. No daemon, no lock-in.
MCP Security Weekly
Get CVE alerts and security updates for io.github.timescale/tiger-skills and similar servers.
Start a conversation
Ask a question, share a tip, or report an issue.
Sign in to join the discussion.
Emulate Claude Skills with any LLM via a Model Context Protocol (MCP) server.
Skills are modular components that enhance the capabilities of an MCP-compatible agent by providing specific functionalities, workflows, and domain expertise. They transform a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.
The goal is to be fully compatible with Anthropic's skill format. See their Agent Skills Spec and related documentation for more details.
Skills are modular, self-contained packages that extend agent capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform the agent from a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.
Every skill consists of a required SKILL.md file and optional bundled resources:
skill-name/
├── SKILL.md (required)
│ ├── YAML frontmatter metadata (required)
│ │ ├── name: (required)
│ │ └── description: (required)
│ └── Markdown instructions (required)
└── Bundled Resources (optional)
├── scripts/ - Executable code (Python/Bash/etc.)
├── references/ - Documentation intended to be loaded into context as needed
└── assets/ - Files used in output (templates, icons, fonts, etc.)
Metadata Quality: The name and description in YAML frontmatter determine when the agent will use the skill. Be specific about what the skill does and when to use it. Use the third-person (e.g. "This skill should be used when..." instead of "Use this skill when...").
scripts/)Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
scripts/rotate_pdf.py for PDF rotation tasksreferences/)Documentation and reference material intended to be loaded as needed into context to inform the agent's process and thinking.
references/finance.md for financial schemas, references/mnda.md for company NDA template, references/policies.md for company policies, references/api_docs.md for API specifications