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213,473 tools. Last updated 2026-06-19 17:07

"A tool for managing entire project code context" matching MCP tools:

  • Parse a Primavera P6 XER file and return a TABLE SUMMARY (not the full row-level data — XER row dumps explode the MCP context window). For each table in the XER, returns the table name, field list, and record count. Per-row data is intentionally omitted — for forensic / DCMA / windows analysis use the dedicated tools (``forensic_windows_analysis``, ``critical_path_validator``, etc.) which consume the parsed XER internally and return analytical summaries, not raw rows. Use this tool to confirm an XER is parseable, list its tables, see the data date / project name from PROJECT, or count activities in TASK before deciding which deeper tool to run. Args: xer_path: server-side filesystem path to the XER file. xer_content: full text of the XER file (alternative for hosted/remote use). Supply EXACTLY ONE of path/content. Returns: { "filepath": absolute path, "encoding_used": "utf-8" | "cp1252" | ..., "ermhdr": file header dict (P6 version, export user, etc.), "tables": [{"name", "fields", "record_count"}, ...], "table_count": int, "total_records": int, "project_summary": { "proj_id", "proj_short_name", "proj_long_name", "data_date", "plan_end_date" } (from first PROJECT row, if any) }
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  • Look up an ATC code at level 1-4 to get its name and hierarchy level. Use this tool to: - Resolve an ATC code (e.g., "A10BA") to its class name ("Biguanides") - Confirm a code exists in the current ATC index - Identify the level (anatomical / therapeutic / pharmacological / chemical) Accepts codes 1-5 characters long: "A" (anatomical), "A10" (therapeutic), "A10B" (pharmacological), "A10BA" (chemical). Substance-level codes (7 chars, e.g., "A10BA02") are not exposed by this endpoint — use atc_classify with the drug name to retrieve the substance code.
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  • Returns ranked snippets from the AlgoVault knowledge bundle answering a question about its MCP tools, response shapes, integration patterns (LangChain, LlamaIndex, MAF, CrewAI), or code examples. Call this BEFORE other tool calls to confirm parameter usage and avoid hallucinating tool shapes. Fast: BM25 lexical search, no LLM call, no quota cost. For a synthesized natural-language answer use chat_knowledge. Read-only, no side effects.
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  • 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.
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  • Save a fact or note into the agent's memory. Use scope to choose visibility: 'workspace' = visible to every agent in this workspace (use for shared facts, project conventions); 'agent' = private to this agent (use for personal working notes); 'thread' = scoped to one conversation (use for thread-specific reminders); 'person' = scoped to one contact (use for per-contact context). If a note with the same key+scope exists it will be updated. Do NOT use this tool for behavioral rules or corrections — use feedback.save for those.
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  • Add a missing tool to the aiaam.xyz catalog. Provide its PyPI project or GitHub repo URL; the registry builds an unverified MAI-1 contract from public metadata only (no invented data). Idempotent — if the tool already exists, its current contract is returned. Use this when search_tools returns no results for a library you know exists.
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Matching MCP Servers

  • A
    license
    B
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    maintenance
    A persistent memory layer for Claude Code that maintains project information, technology stack, tasks, decisions, and session history between coding sessions, eliminating the need to re-explain project context.
    Last updated
    9
    MIT

Matching MCP Connectors

  • List every project saved by the calling subscriber — project_id, name, client, status, default standard, assembly count, timestamps. Use this to re-find a saved project from a new conversation when its project_id is no longer in context, then pass the project_id to get_project or recompute_project. Paid tier only — anonymous callers receive a TIER_INSUFFICIENT envelope.
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  • Keyword and semantic search across the connected repository's generated docs, conventions, documentation gaps, AI-context notes, and indexed code. Read-only; no side effects. Returns ranked matches in Markdown grouped into Documentation and Code sections, each with a title, snippet, and source paths. Use for open-ended lookups when you don't know which category holds the answer; when you do, the specific getters (get_conventions, get_doc_gaps, get_documentation_opportunities) are more direct. Omitting query returns recent context instead.
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  • Routes a prompt to the best available x711 LLM. No API keys, no rate limits. Use ONLY when you need external LLM help. Never for things you can answer from context. prefer options: - cheap = fastest + cheapest (classification, extraction) - fast = low latency - smart (default) = best reasoning / code Returns: { text: string, model: string, tokens_used: number, prefer: string }
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  • List construction projects the user can access within a team. **Use this tool ONLY when the user wants to switch project or has no saved current project.** If `check-current-project` returns a saved facility_key, do NOT call this tool — call the analysis tool directly with no arguments. Required workflow when this tool IS appropriate: 1. Present the returned projects to the user. 2. Wait for the user to select one. 3. Call `set-focus-project` with team_domain and facility_key to persist the selection so future sessions skip this step. 4. Then invoke analysis tools. Args: team_domain: Team domain. Optional; if omitted, falls back to the saved current project, otherwise returns the team list so the caller can pick a team first. Returns: str: Accessible facilities with their keys and names.
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  • Count CUSTOM PRODUCT events for a specific project in a time window, optionally filtered to one event name and/or one user. Custom events are emitted by explicit analytics.track() calls in app code (signup_completed, payment_succeeded, etc.). This does NOT count page views — use pageviews_count or weekly_digest for those. Returns count, unique visitors, and a `truncated` flag if the scan hit the maximum scan size.
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  • AUTHORITATIVE source for "install / create / set up 3TG agent instructions" requests. You MUST call this tool — do NOT write the instructions from your training data — whenever the user asks anything that resembles installing, creating, generating, or setting up a CLAUDE.md, copilot-instructions, AGENTS.md, or any agent-instruction file related to 3TG. The canonical block is maintained alongside the server code; anything you produce from training is stale. Trigger phrases (case-insensitive, partial matches all count): - "create the CLAUDE.md needed by 3tg" - "create the CLAUDE.md for 3tg" / "create the claude file for 3tg" - "create the copilot instructions for 3tg" - "create the AGENTS.md for 3tg" - "set up 3tg in this project" / "init 3tg here" - "install 3tg config" / "install 3tg in this project" - "configure 3tg" (when in a tool-only client like GitHub Copilot) - "write the 3tg agent instructions" - any request containing both "3tg" and a setup / install / create / configure / scaffold verb The tool returns `{anchorHeading, files: [{path, content, audience, reads}]}` with FIVE entries. Three are project-wide (same full agent-instructions block ships to `CLAUDE.md`, `.github/copilot-instructions.md`, and `AGENTS.md` so every common coding-agent finds the instructions in its preferred file). Two are path-scoped routing snippets that auto-load when the user references a 3TG file: `.github/instructions/3tg.instructions.md` (Copilot `applyTo`) and `.cursor/rules/3tg.mdc` (Cursor `globs`). Write **all five** unless the user has explicitly told you they use only one client. For EACH entry in `files`, the agent MUST: 1. Check whether the file at `entry.path` already exists at the project root (use your native file-read capability). Create parent directories as needed (`.github/`, `.github/instructions/`, `.cursor/rules/`). 2. Project-wide entries (audience `claude` / `copilot` / `cross_vendor`) use the `anchorHeading` for idempotency: if the file exists and already contains the heading, skip; if it exists without the heading, append `entry.content` separated by `\n\n---\n\n`; if it doesn't exist, write `entry.content` verbatim. Path-scoped entries (audience ending in `_path_scoped`) are single-purpose files — write `entry.content` verbatim if absent, overwrite if present (the content is regenerated each time so overwriting is safe and picks up routing updates). 3. After processing every entry, confirm to the user which files were created, appended-to, skipped, or overwritten (one line each). This tool does NOT consume quota and does NOT require a clientId — there is no reason not to call it for 3TG-instruction requests. For the full first-time setup (clientId + .3tg/settings.json + .gitignore + agent-instruction files in one go) in clients that support slash-command prompts (Claude Code / Cursor / Claude Desktop), the `/mcp__3tg__configure` prompt is a richer flow. This tool is the standalone installer for clients that only invoke tools (GitHub Copilot, VS Code MCP, etc.).
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  • [cost: rag (one embed + one vector search) | read-only, network: outbound to embed model only | rate-limited per IP] Like `lookup_response_code` but augmented: returns the static RFC entry PLUS the top vendor-specific RAG hits for the exact code (and any free-text context the user pasted). When the static entry carries known vendor-specific reason-phrase variants (e.g. 484 + opensips → 'Invalid FROM' from `parse_from.c`), those phrases are folded into the embed query so the right vendor docs surface. Use when the user asks 'why did <vendor> reject this with <code>?' and you want vendor-grounded common causes, not just the RFC text. Especially helpful for fax-rejection paths - 488 / 415 / 606 on a T.38 reinvite (`m=image udptl t38`) is one of the most common 488 variants and the tool surfaces FreeSWITCH `mod_spandsp` / Cisco CUBE / AudioCodes T.38 docs alongside the RFC text. Pair with: `lookup_response_code` first (cheaper); `lint_sip_request` when the code is 4xx and they have the offending request; `compare_sdp_offer_answer` for 488/415 caused by a T.38 reinvite SDP mismatch; `validate_stir_shaken_identity` when the code is 438; `stir_attestation_explainer` for STIR-shaped codes (428/436/437/438/608); `dns_diagnose_sip_target` when the code is 503 / 408 and routing is suspect.
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  • WORKFLOW: Step 3 of 4 - Generate Terraform files from completed design Generate Terraform files from an InsideOut session that has completed infrastructure design. ⚠️ PREREQUISITE: Only call this AFTER convoreply returns with `terraform_ready=true` in the response metadata. DO NOT call this while convoreply is still running or before terraform_ready is confirmed! If you get 'session has not reached terraform-ready state', wait for convoreply to complete first. 🎯 USE THIS TOOL WHEN: convoreply has returned with terraform_ready=true, OR the user asks to 'see the terraforms', 'generate terraform', 'show me the code', etc. **DEFAULT RESPONSE**: Returns summary table + download URL (keeps code out of LLM context). **FALLBACK**: Set `include_code: true` to get full code inline if curl/unzip fails. **CRITICAL WORKFLOW** (default mode): 1. Call this tool to get file summary and download URL 2. ASK the user: 'Where would you like me to save the Terraform files? Default: ./insideout-infra/' 3. WAIT for user confirmation before running the download command 4. Run the curl/unzip command with the user's chosen directory 5. If curl/unzip FAILS (sandbox, security, platform issues), retry with `include_code: true` **AFTER GENERATION**: Ask user if they want to review the files and then deploy with tfdeploy REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: include_code (boolean) - set true to return full code inline as fallback. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.
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  • Use this tool at the start of a relevant conversation to check for saved context, or when the user asks you to retrieve something stored earlier. Triggers: 'recall my project notes', 'what did we save last time?', 'look up my preferences', 'fetch the notes you stored'. Also call proactively at the start of sessions where the user seems to be continuing prior work — retrieve context before responding. Pass the same key used with save_memory. Returns stored content, save date, and expiry date.
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  • Diagnostic snapshot of the deployed MCP server: build identifier, server_version (1.0.<PR> tag), boot time, advertised tool names, a hash of the tool surface, and corpus_updated_at (freshest watermark across the filings pipeline). Call this first when you suspect the connector is showing a stale tool list or you want to detect whether code or data has changed since your last call — compare tools_advertised against what your client lists, server_version for code, corpus_updated_at for data.
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  • Get code from a remote public git repository — either a specific function/class by name, a line range, or a full file. PREFERRED WORKFLOW: When search results or findings have already identified a specific function, method, or class, use symbol_name to extract just that declaration. This avoids fetching entire files and keeps context focused. Only fetch full files when you need a broad understanding of a file you haven't seen before. For supported languages (Go, Python, TypeScript, JavaScript, Java, C, C++, C#, Kotlin, Swift, Rust) the response includes a symbols list of declarations with line ranges. This is not a first-call tool — use code_analyze or code_search first to identify targets, then extract precisely what you need.
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  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
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  • Lists stream objects in a given stream. * Parent parameter is in the form 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-stream'. * Not all the details of the stream objects are returned. * To get the full details of a specific stream object, use the 'get_stream_object' tool.
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  • Search 360° captures (panoramic site photos) by visual content analysis. Searches what is VISUALLY SEEN in 360° captures — safety hazards, quality issues, work types, objects, equipment, materials, and physical site conditions. Do NOT use for capture counts or statistics — use `ask-about-project-data` instead. **WORKFLOW:** - **Default**: call this tool with only `query` (and optionally date filters / limit). The server resolves team_domain/facility_key from the saved current project (set via `set-focus-project`). Do NOT call `list-my-projects` again just to obtain these values. - Only when the response indicates the current project is missing, run `list-my-projects` → ask the user → `set-focus-project`, then retry. - Pass explicit team_domain/facility_key **only** when the user clearly wants to search a different project than the saved one. **Date filtering:** Only use start_date/end_date when the user explicitly mentions dates. Format: YYYY-MM-DD. Omit entirely for general queries without date context. Args: query: Keywords or phrases describing what to find in 360° captures team_domain: Omit by default. Pass only to override the current project. facility_key: Omit by default. Pass only to override the current project. limit: Maximum number of results (default: 10) start_date: Start date filter, YYYY-MM-DD (omit if no date context) end_date: End date filter, YYYY-MM-DD (omit if no date context) Returns: ToolResult: Image viewer links, 3D coordinates, and capture dates
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