Skip to main content
Glama
306,903 tools. Last updated 2026-07-16 21:48

"namespace:io.github.tide-foundation" matching MCP tools:

  • List available app templates with IDs and summaries to select a foundation for a new Cloudflare app before inspecting, composing, or generating.
    MIT
  • Retrieve your starred companies and audit them for tech stack alignment. Suggests unstarring mismatched ones and finding better matches.
    MIT
  • Start a new Tenzir package project by setting up the standard directory structure for operators, tests, and documentation, and initializing package metadata.
    Apache 2.0
  • Retrieve Kronos shadow-mode prediction statistics per bot, including agreement rate, direction accuracy, and promotion readiness against the Bayesian ensemble. Read-only observer with no impact on live trades.
    MIT

Matching MCP Servers

Matching MCP Connectors

  • Foundation discovery and grant intelligence for nonprofits. 174K+ US funders, IRS 990 data.

  • MCP server teaching AI agents to implement TideCloak: auth, E2EE, IGA, security analysis

  • Manage bexio accounting data: chart of accounts, account groups, calendar years, VAT periods, taxes, and journal entries using list, search, create, and delete actions.
    MIT
  • Create a canon by repeating a melody across multiple voices with delayed entries and optional transposition. Ideal for composing contrapuntal music like rounds or fugues.
    Apache 2.0
  • Generate complete design systems by combining styles, colors, typography, and layout patterns for web or mobile projects. Auto-detects platform and intent to provide cohesive design foundations.
    MIT
  • Render hero metric widgets for KPIs: big number, progress ring, status, comparison, rank, countdown, threshold, breakdown, NPS, orb, or gem. Pick variant based on the question you need answered.
    Functional Source , Version 1.1, MIT Future
  • Reads project manifests and config files to detect framework, language, styling system, component file extensions, and SVG handling.
    MIT
  • Selects the mathematically optimal context subset within a token budget by scoring fragments on recency, frequency, semantic similarity, and information density. Automatically expands vague queries to improve selection accuracy.
    Apache 2.0