timescale/tiger-skills-mcp-server

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SkillsMP-Katalog aktualisiert: 2. November 2026 um 18:02

gesammelte Skills: 1

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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/timescale/tiger-skills-mcp-server.

README des Repositorys

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# Tiger Skills MCP Server Emulate Claude Skills with any LLM via a [Model Context Protocol](https://modelcontextprotocol.io/introduction) (MCP) server. ## What are Skills? 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](https://github.com/anthropics/skills/blob/main/agent_skills_spec.md) and related documentation for more details. <details> <summary><strong>An overview of the Skills spec</strong></summary> ### Skill Structure 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. ### What Skills Provide 1. Specialized workflows - Multi-step procedures for specific domains 2. Tool integrations - Instructions for working with specific file formats or APIs 3. Domain expertise - Company-specific knowledge, schemas, business logic 4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks ### Anatomy of a Skill Every skill consists of a required SKILL.md file and optional bundled resources: ```text 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.) ``` #### SKILL.md (required) **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..."). #### Bundled Resources (optional) ##### Scripts (`scripts/`) Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten. - **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed - **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks - **Benefits**: Token efficient, deterministic, may be executed without loading into context - **Note**: Scripts may still need to be read by the agent for patching or environment-specific adjustments ##### References (`references/`) Documentation and reference material intended to be loaded as needed into context to inform the agent's process and thinking. - **When to include**: For documentation that the agent should reference while working - **Examples**: `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 - **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides - **Benefits**: Keeps SKILL.md lean, loaded only when the agent determines it's needed - **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md - **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files. ##### Assets (`assets/`) Files not intended to be loaded into context, but rather used within the output the agent produces. - **When to include**: When the skill needs files that will be used in the final output - **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography - **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified - **Benefits**: Separates output resources from documentation, enables the agent to use files without loading them into context ### Progressive Disclosure Design Principle Skills use a three-level loading system to manage context efficiently: 1. **Metadata (name + description)** - Always in context (~100 words) 2. **SKILL.md body** - When skill triggers (<5k words) 3. **Bundled resources** - As needed by the agent (Unlimited\*) \*Unlimited because scripts can be executed without reading into context window. </details> ## Configuration ### Environment Variables - `SKILLS_FILE`: Path to the YAML file configuring the set of skills. Default: `./skills.yaml` - `SKILLS_TTL`: Time (in milliseconds) to cache loaded skills. Default: 5 minutes ### Skills Configuration File The set of skills is configured via a YAML file. Both local directories and GitHub repositories are supported. Config can point to individual skills or collections of skills. ```yaml local-directory-collection: # A collection of local skills stored in the `./skills` directory. # Each skill should be in its own subdirectory with a `SKILL.md` file. type: local_collection path: ./skills local-individual-skill: # An individual local skill stored in the `./skills/skill-name` directory. type: local path: ./path-to/individual/skill-name anthropic-github-collection: # A GitHub repo containing a collection of skills. # Each skill should be in its own subdirectory with a `SKILL.md` file. type: github_collection repo: anthropics/skills # path: ./ # not needed for this example since skills are at the root of the repo # Optionally specify skills/paths to ignore in this collection ignored_paths: - .claude-plugin - document-skills disabled_skills: - canvas-design # Setting enabled_skills will _only_ load the specified skills from the collection # enabled_skills: # - frontend-design # - webapp-testing single-github-skill-example: # A GitHub repo containing an individual skill. type: github repo: anthropics/claude-cookbooks path: ./skills/custom_skills/creating-financial-models ``` Skill names must be unique across all configured skills. Any duplicates will be ignored with a warning. ### Connection string parameters Individual clients can control the set of skills that are enabled, as well as the protocol(s) used, via parameters in the connection string. - `enabled_skills`: Comma-separated list of skill keys to enable. If not provided, all configured skills are enabled. - `disabled_skills`: Comma-separated list of skill keys to disable. If not provided, no skills are disabled. - `tools=0`: Disable all tools (for resource-only integration). - `resources=0`: Disable all resources (for tool-only integration). #### Example ```text http://tiger-skills-mcp-server/mcp?disabled_skills=foo,bar&resources=0 ``` ## Subagent Task Execution This MCP server (optionally) provides a `subagent` tool that can be used to break up complex tasks into smaller subtasks, each handled by its own agent instance. This is useful for tasks that require multiple steps, especially when those steps may require consuming large amounts of data in LLM context. The subagent will automatically have access to the same set of skills as configured for the `view` skill tool, as well as the ability to (recursively) invoke further subagents. In addition, a `mcp.yaml` configuration file can be provided to specify additional tooling to be made available to the subagent. If you do not wish to use subagents, you can set `SUBAGENT_DISABLED=true` in the environment to disable the tool. ### MCP Configuration for Subagents Create a `mcp.yaml` file to specify additional tools for the subagent to have accessible. This file is read from the root directory by default, or you can specify a different path via the `MCP_PATH` environment variable. Only the streamable HTTP transport is supported at this time. ```yaml pg_aiguide: type: http url: https://mcp.tigerdata.com/docs ``` ## Development Cloning and running the server locally. ```bash git clone git@github.com:timescale/tiger-skills-mcp-server.git ``` ### Building Run `./bun i` to install dependencies and build the project. Use `./bun watch` to rebuild on changes. You will need a GitHub token with the correct scopes. Here is a direct link to [create such a new token](https://github.com/settings/tokens/new?scopes=repo,read:org,read:user,user:email&description=tiger-skills-mcp-server). Create a `.env` file based on the `.env.sample` file. ```bash cp .env.sample .env ``` Then update the `GITHUB_TOKEN` value in `.env`. ### Testing The MCP Inspector is a very handy to exercise the MCP server from a web-based UI. ```bash ./bun inspector ``` #### Test via HTTP ```bash ./bun watch http ``` | Field | Value | | -------------- | --------------------------- | | Transport Type | `Streamable HTTP` | | URL | `http://localhost:3001/mcp` | #### Test via stdio ```bash ./bun watch stdio ``` | Field | Value | | -------------- | --------------- | | Transport Type | `STDIO` | | Command | `node` | | Arguments | `dist/index.js` | #### Testing in Claude Desktop Create/edit the file `~/Library/Application Support/Claude/claude_desktop_config.json` to add an entry like the following, making sure to use the absolute path to your local `tiger-skills-mcp-server` project, and use a valid GitHub token. ```json { "mcpServers": { "tiger-skills": { "command": "node", "args": [ "/absolute/path/to/tiger-skills-mcp-server/dist/index.js", "stdio" ], "env": { "GITHUB_TOKEN": "ghp_whatever" } } } } ```

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Quellsprache: Englisch

2025-11-18

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