Skip to main content
Glama
127,309 tools. Last updated 2026-05-05 13:48

"Tool to analyze backend code, connect with Jira, and automate coding tasks" matching MCP tools:

  • Search for medical procedure prices by code or description. Use this for direct lookups when you know a CPT/HCPCS code (e.g. "70551") or want to search by keyword (e.g. "MRI", "knee replacement"). For code-like queries → exact match on procedure code. For text queries → searches code, description, and code_type fields. Supports filtering by insurance payer, clinical setting, and location (via zip code or lat/lng coordinates with a radius). NOTE: Results are from US HOSPITALS only — not non-US providers, independent imaging centers, ambulatory surgery centers (ASCs), or other freestanding facilities. Args: query: CPT/HCPCS code (e.g. "70551") or text search (e.g. "MRI brain"). Must be at least 2 characters. code_type: Filter by code type: "CPT", "HCPCS", "MS-DRG", "RC", etc. hospital_id: Filter to a specific hospital (use the hospitals tool to find IDs). payer_name: Filter by insurance payer name (e.g. "Blue Cross", "Aetna"). plan_name: Filter by plan name (e.g. "PPO", "HMO"). setting: Filter by clinical setting: "inpatient" or "outpatient". zip_code: US zip code for geographic filtering (alternative to lat/lng). lat: Latitude for geographic filtering (use with lng and radius_miles). lng: Longitude for geographic filtering (use with lat and radius_miles). radius_miles: Search radius in miles from the zip code or lat/lng location. page: Page number (default 1). page_size: Results per page (default 25, max 100). Returns: JSON with matching charge items including procedure codes, descriptions, gross charges, cash prices, and negotiated rate ranges per hospital.
    Connector
  • Create multiple tasks in a single operation with escrow calculation. ⚠️ **WARNING**: This tool BYPASSES the standard payment flow by calling db.create_task() directly instead of using the REST API (POST /api/v1/tasks). This means it skips x402 payment verification and balance checks. For production use, tasks should be created via the REST API to ensure proper payment authorization and escrow handling. Supports two operation modes: - ALL_OR_NONE: Atomic creation (all tasks or none) - BEST_EFFORT: Create as many as possible Process: 1. Validates all tasks in batch 2. Calculates total escrow required 3. Creates tasks (atomic or best-effort) - **BYPASSING PAYMENT FLOW** 4. Returns summary with all task IDs Args: params (BatchCreateTasksInput): Validated input parameters containing: - agent_id (str): Your agent identifier - tasks (List[BatchTaskDefinition]): List of tasks (max 50) - payment_token (str): Payment token (default: USDC) - operation_mode (BatchOperationMode): all_or_none or best_effort - escrow_wallet (str): Optional custom escrow wallet Returns: str: Summary of created tasks with IDs and escrow details.
    Connector
  • Create multiple tasks in a single operation with escrow calculation. ⚠️ **WARNING**: This tool BYPASSES the standard payment flow by calling db.create_task() directly instead of using the REST API (POST /api/v1/tasks). This means it skips x402 payment verification and balance checks. For production use, tasks should be created via the REST API to ensure proper payment authorization and escrow handling. Supports two operation modes: - ALL_OR_NONE: Atomic creation (all tasks or none) - BEST_EFFORT: Create as many as possible Process: 1. Validates all tasks in batch 2. Calculates total escrow required 3. Creates tasks (atomic or best-effort) - **BYPASSING PAYMENT FLOW** 4. Returns summary with all task IDs Args: params (BatchCreateTasksInput): Validated input parameters containing: - agent_id (str): Your agent identifier - tasks (List[BatchTaskDefinition]): List of tasks (max 50) - payment_token (str): Payment token (default: USDC) - operation_mode (BatchOperationMode): all_or_none or best_effort - escrow_wallet (str): Optional custom escrow wallet Returns: str: Summary of created tasks with IDs and escrow details.
    Connector
  • Get tasks from the Execution Market system with optional filters. Use this to monitor your published tasks or browse available tasks. Args: params (GetTasksInput): Validated input parameters containing: - agent_id (str): Filter by agent ID (your tasks only) - status (TaskStatus): Filter by status (published, accepted, completed, etc.) - category (TaskCategory): Filter by category - limit (int): Max results (1-100, default 20) - offset (int): Pagination offset (default 0) - response_format (ResponseFormat): markdown or json Returns: str: List of tasks in requested format. Examples: - Get my published tasks: agent_id="0x...", status="published" - Get all completed tasks: status="completed" - Browse physical tasks: category="physical_presence"
    Connector
  • Add one or more tasks to an event (task list). Supports bulk creation. IMPORTANT: Set response_type correctly — use "text" for info collection (names, phones, emails, notes), "photo" for visual verification (inspections, serial numbers, damage checks), "checkbox" only for simple confirmations. NOTE: To dispatch tasks to the Claude Code agent running on Mike's PC, use tascan_dispatch_to_agent instead — it routes directly to the agent's inbox with zero configuration needed.
    Connector
  • Connect to the user's catalogue using a pairing code. IMPORTANT: Most users connect via OAuth (sign-in popup) — if get_profile already works, the user is connected and you do NOT need this tool. Only use this tool when: (1) get_profile returns an authentication error, AND (2) the user shares a code matching the pattern WORD-1234 (e.g., TULIP-3657). Never proactively ask for a pairing code — try get_profile first. If the user does share a code, call this tool immediately without asking for confirmation. Never say "pairing code" to the user — just say "your code" or refer to it naturally.
    Connector

Matching MCP Servers

Matching MCP Connectors

  • Jira MCP Pack

  • AI-native art catalogue. Catalogue works, parse provenance, and generate signed RAIs.

  • WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.
    Connector
  • WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.
    Connector
  • Wait for the user to securely connect their cloud account and subscribe to Luther Systems. Polls until credentials appear on the session. 🎯 USE THIS TOOL WHEN: tfdeploy returns an 'auth_required', 'no_credentials', or 'credentials_expired' error. The user needs to visit the connect URL to: 1. Connect their cloud credentials (AWS or GCP) 2. Sign up and subscribe to a Luther Systems plan (required for deployment) This secure connection allows InsideOut to deploy and manage infrastructure in the user's cloud account on their behalf. Credentials are handled securely and only used for deployment and management sessions. WORKFLOW: 1. FIRST: Present the connect URL and explanation to the user (from the tfdeploy error response) 2. THEN: Call this tool to begin polling for credentials 3. The user opens the URL in their browser to subscribe and add credentials 4. When credentials are found, inform the user and call tfdeploy to deploy IMPORTANT: Do NOT call this tool without first showing the connect URL to the user. The user needs to see the URL to complete the process. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: cloud ('aws' or 'gcp'), timeout (integer, seconds to wait, default 300, max 600).
    Connector
  • Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.
    Connector
  • Wait for the user to securely connect their cloud account and subscribe to Luther Systems. Polls until credentials appear on the session. 🎯 USE THIS TOOL WHEN: tfdeploy returns an 'auth_required', 'no_credentials', or 'credentials_expired' error. The user needs to visit the connect URL to: 1. Connect their cloud credentials (AWS or GCP) 2. Sign up and subscribe to a Luther Systems plan (required for deployment) This secure connection allows InsideOut to deploy and manage infrastructure in the user's cloud account on their behalf. Credentials are handled securely and only used for deployment and management sessions. WORKFLOW: 1. FIRST: Present the connect URL and explanation to the user (from the tfdeploy error response) 2. THEN: Call this tool to begin polling for credentials 3. The user opens the URL in their browser to subscribe and add credentials 4. When credentials are found, inform the user and call tfdeploy to deploy IMPORTANT: Do NOT call this tool without first showing the connect URL to the user. The user needs to see the URL to complete the process. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: cloud ('aws' or 'gcp'), timeout (integer, seconds to wait, default 300, max 600).
    Connector
  • Associate an email and handle with your account. Step 1: Call with just email — sends a 6-digit verification code. Step 2: Call with email + code + handle — verifies and completes setup. This lets you log in to the console and sets your permanent @handle.
    Connector
  • PRIMARY TOOL - Call this at the START of every conversation to load comprehensive user context. Returns: - current_datetime: Current date and time in the user's timezone (ISO 8601 with offset) - All active facts about the user (preferences, personal info, relationships) - tasks_overdue: Tasks with scheduled_date OR deadline in the past - tasks_today: Tasks scheduled OR due today (time >= now), plus unscheduled tasks (no date set) - tasks_tomorrow: Tasks scheduled OR due tomorrow (includes projected recurring tasks) - Active goals - Recent moments from the last 5 days - Latest 15 user-facing notes (id + description). Use get_note to retrieve full content. - ai_memory: Latest 15 AI memory notes from your previous sessions (id + description). Use get_note to retrieve full content. SELF-LEARNING: Review the ai_memory array — these are notes you saved in previous sessions about how to best assist this user. Load relevant ones with get_note. Throughout the conversation, save new learnings anytime via save_note with scope="ai_client" whenever you discover something worth remembering. - tasks_recently_completed: Tasks completed or skipped in the last 7 days Each task includes: - category_reason: 'scheduled' | 'deadline' | 'both' - explains why it's in that array - has_scheduled_time: true if task has a specific scheduled time, false if all-day - has_deadline_time: true if deadline has a specific time, false if all-day Task placement uses scheduled_date when present, otherwise deadline. Each task appears in exactly one category. For calendar events, the user should connect a calendar MCP (Google Calendar MCP, Outlook MCP) in their AI client. Query those MCPs alongside Anamnese for a complete daily view. This provides essential grounding for personalized, context-aware conversations.
    Connector
  • The unit tests (code examples) for HMR. Always call `learn-hmr-basics` and `view-hmr-core-sources` to learn the core functionality before calling this tool. These files are the unit tests for the HMR library, which demonstrate the best practices and common coding patterns of using the library. You should use this tool when you need to write some code using the HMR library (maybe for reactive programming or implementing some integration). The response is identical to the MCP resource with the same name. Only use it once and prefer this tool to that resource if you can choose.
    Connector
  • Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.
    Connector
  • Generate SDK scaffold code for common workflows. Returns real, indexed code snippets from GitHub with source URLs for provenance. Use this INSTEAD of hand-coding SDK calls — hand-coded Senzing SDK usage commonly gets method names wrong across v3/v4 (e.g., close_export vs close_export_report, init vs initialize, whyEntityByEntityID vs why_entities) and misses required initialization steps. Languages: python, java, csharp, rust. Workflows: initialize, configure, add_records, delete, query, redo, stewardship, information, full_pipeline (aliases accepted: init, config, ingest, remove, search, redoer, force_resolve, info, e2e). V3 supports Python and Java only. Returns GitHub raw URLs — fetch each snippet to read the source code.
    Connector
  • Recommends a complete stack from BuyAPI's corpus with a structured decision matrix, cost estimate, assumptions, unknowns, alternatives, and sources. Use this when the user is starting a project or asks for a complete stack choice. Do not use this for local coding/debugging/docs questions that do not involve software or vendor selection. Do not call vendors.resolve first; this tool handles retrieval and ranking.
    Connector
  • AZURE DEVOPS ONLY -- Query Work Items (Bugs, Tasks, FDDs, User Stories, CRs) in Azure DevOps. [~] PRIORITY TRIGGER: use this tool when the user mentions 'FDD', 'RDD', 'IDD', 'CR', 'Task', 'Workitem', 'Work Item', 'Bug', 'User Story', 'Feature', 'Issue', 'ticket', 'sprint', 'backlog', 'DevOps', 'liste des tâches', 'show tasks', 'find bugs', '#1234', 'WI#'. NEVER use this tool for: D365 labels (@SYS/@TRX), X++ code, AOT objects, tables, classes, forms, enums, error messages, 'c\'est quoi le label', 'search_labels', 'libellé', 'label D365'. For labels -> use search_labels. For D365 code -> use search_d365_code or get_object_details. Shortcuts: 'bugs' (all active bugs), 'my bugs' (assigned to me), 'recent' (updated last 7 days), 'sprint' (current iteration). Or pass any WIQL SELECT statement or a free-text title search. Use '*' with filters only. Returns max 50 work items with ID, title, type, state, priority, area, assigned-to. Requires DEVOPS_ORG_URL + DEVOPS_PAT env vars.
    Connector
  • Given a svelte component or module returns a list of suggestions to fix any issues it has. This tool MUST be used whenever the user is asking to write svelte code before sending the code back to the user
    Connector
  • Search recipes by keyword across titles, descriptions, tags, and full source code. Use for any iOS, SwiftUI, or backend topic — e.g. subscription, authentication, camera, animation, chart, onboarding, paywall, infrastructure.
    Connector