Server data from the Official MCP Registry
Canadian procurement intelligence: CanadaBuys and Alberta tenders, ranked for your shop.
Canadian procurement intelligence: CanadaBuys and Alberta tenders, ranked for your shop.
Remote endpoints: streamable-http: https://elbowsupknivesout.warreandvavasour.com/mcp
WorkspaceAlberta is a legitimate procurement intelligence MCP server with reasonable architecture and no obvious malicious intent. However, several security concerns lower the score: unauthenticated API access to sensitive government procurement data, inadequate input validation on user-supplied profiles and search parameters, missing rate limiting on external API calls, and credential handling that relies on environment variables without explicit validation. The service's permissions (network access to government APIs, file I/O, environment variable reading) align with its stated purpose, but the lack of authentication boundaries on the hosted endpoint and insufficient safeguards against parameter injection create moderate risk. Supply chain analysis found 5 known vulnerabilities in dependencies (0 critical, 5 high severity). Package verification found 1 issue.
4 files analyzed · 16 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
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Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
The hosted MCP server is live and free for browsing — no install, no account, no API key. Point any MCP-capable assistant at it:
https://elbowsupknivesout.warreandvavasour.com/mcp
Cursor, Claude Code, and other HTTP-native clients — add to your MCP config:
{
"mcpServers": {
"workspacealberta": {
"url": "https://elbowsupknivesout.warreandvavasour.com/mcp"
}
}
}
Claude Desktop (no native HTTP transport) — bridge with mcp-remote:
{
"mcpServers": {
"workspacealberta": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://elbowsupknivesout.warreandvavasour.com/mcp"]
}
}
}
Then ask it something a real owner would ask:
Run it locally instead (the whole server is pure Python):
python -m pip install -r requirements.txt
python mcp-servers/canadabuys/server.py
Smoke test: python -m unittest tests.test_canadabuys_mcp_smoke. Client config variants live in mcp.json.example; full tool and REST reference in docs/mcp-tool-reference.md.
WorkspaceAlberta is a Canadian procurement intelligence workspace. It connects public tender data to the people who can actually do the work: fabricators, mills, contractors, shops, manufacturers, and the small teams that keep the real economy moving.
The direction is explicit:
command-a-plus-05-2026, with the W4A4 Hugging Face route available through CohereLabs/command-a-plus-05-2026-w4a4.The point is not nationalism as decoration. The point is operational independence.
If Canadian companies are going to bid Canadian work, understand Canadian supply chains, and protect Canadian industrial capacity, then the AI layer underneath that work matters.
AI promised 5X productivity. Most small businesses got a chatbot that writes mediocre marketing copy.
The model is not the whole bottleneck. The connection is.
Wiring up the places where the work lives usually costs money, time, and technical patience a small business does not have. Government tender databases are a perfect example: the work is public, the demand is real, but the discovery process is still awkward enough that good companies miss good opportunities.
WorkspaceAlberta solves the last mile by giving an AI assistant the wiring it needs to search, compare, summarize, and brief public procurement opportunities from inside the workspace where the owner is already working.
WorkspaceAlberta is an MCP-first workspace for Canadian procurement.
It now brings together:
The assistant can:
This is meant to answer practical questions:
The custom MCP server is the product.
It is a deployed working endpoint that knows the live public procurement pipeline exposed by CanadaBuys and Alberta Purchasing Connection. It can serve that pipeline back to users through an AI assistant based on what they do, where they work, what they can supply, and what deadlines matter.
The core tools are:
search_opportunities for unified federal and Alberta searchget_opportunity_details for a single posting by reference numberlist_deadlines for what is closing soonfind_matching_opportunities for profile-based rankingdaily_bid_brief for the daily owner/operator summaryanalyze_contract_with_cohere for optional Cohere Command A+ tender reviewprocess_bid_room for live E2B attachment extraction and Cohere tool-assisted bid reviewwatch_opportunity / list_watchlist for a persistent tracking list with closing-date countdownsbid_no_bid_scorecard for a fast deterministic go/caution/no-go read on any referenceThe full tool and REST reference lives in docs/mcp-tool-reference.md; the architecture walkthrough is docs/architecture.md.
MCP is the first-class interface because this is meant to be used by agents. The same procurement core also exposes REST/OpenAPI so other AI tools can hook into the same contract intelligence without needing native MCP support.
Underneath the endpoint is pure Python procurement logic. The data processing, filtering, matching, deadline ranking, and brief generation do not require an LLM. The model layer is added only where judgment helps: risk review, requirements explanation, and bid/no-bid reasoning.
E2B sandboxes are the isolated compute layer for heavier bid-room work: opening tender packages, parsing attachments, extracting compliance requirements, and returning structured bid artifacts without putting unknown user files inside the always-on MCP service. Cohere Command A+ runs inside the short-lived sandbox with read-only evidence tools over the extracted documents. The build plan lives in docs/e2b-bid-room-plan.md, and the business-owner operating diagram lives in docs/bid-room-operating-diagram.md.
Get 50% of the population 10% better. Every year. That is generational growth.
Not 10 developers 500% better. That is happening. But it does not scale to the economy.
"How do I save 5 hours a week?" "How do I save $700 a month?"
Those are the real questions. This is how you answer them.
Alberta's steel, lumber, and metals industries represent over 2,500 companies with a combined economic impact exceeding $37 billion annually.
| Sector | Companies | Economic Impact | Jobs Supported |
|---|---|---|---|
| Forestry & Wood Products | 676+ businesses, 40 major mills | $14 billion | 41,400 |
| Fabricated Metal Products | 1,871 establishments | $23.4B manufacturing sector | 16,600 |
| Primary & Machinery Manufacturing | 200+ facilities | Included above | 12,000+ |
Behind every one of these companies are dozens of systems that need to talk to each other just to get anything done: quoting software, inventory spreadsheets, accounting packages, project trackers, supplier portals, and government tender databases.
Any tool that helps a fabricator create demand, a mill manufacture more efficiently, or a contractor cut costs has multiplier effects across the entire province:
More contracts won. More jobs kept. More skill developed. More value staying here at home.
MCP server:
mcp-servers/canadabuys/server.pymcp-servers/canadabuys/server_http.py for hosted StreamableHTTP MCP plus REST/OpenAPIprocurement_core/service.py for the shared Python procurement coreprocurement_core/e2b_bid_room.py for live E2B bid-room sandbox processingSmoke test:
tests/test_canadabuys_mcp_smoke.pytests/test_procurement_http_app.pypython scripts/e2b_bid_room_smoke.py for a live E2B sandbox testConfiguration:
AGENTS.md for Codex/OpenClaw guidancemcp-servers/canadabuys/README.md for server tools and environment variablesdocs/setup-productization-track.md for the combined WorkspaceAlberta + private wvsetup setup trackdocs/codex-setup.md for local setup notesdocs/workspace-alberta-hermes-install.md for the branded Hermes / Raspberry Pi setup draftData and model sources:
Image source notes live in docs/imagery-sources.md.
The country is traveling west. Domestic travel to the western provinces is scaling, and the properties hosting those travelers run on systems like OPERA Cloud.
The Warre & Vavasour tourism thesis: in an extreme-AI world, people crave the analog. Real places, real adventures. The premium goes to authentic, place-bound experiences — and AI is invisible wiring, not the product.
The wiring problem looks exactly like procurement's last mile. A hotel's own data lives inside OPERA Cloud, and getting it out for analysis usually means expensive middleware or manual exports. Front-desk managers, revenue people, and owners can't use what they can't reach.
So the repo ships a second MCP server: mcp-servers/opera-analytics/server.py, a read-only analytics data tap for OPERA Cloud Reporting & Analytics Data APIs. A property's own user signs in as themselves — OAuth2 password grant, with credentials from the hotel's own OPERA Cloud Developer Portal. No partner program, no middleware vendor.
It covers 75 analytics subject areas — guest/deposit/AR ledgers, transactions, reservation statistics and pace, managers report, history and forecast, rate codes, profiles, blocks, catering events, housekeeping inventory — through 9 tools:
opera_auth_status to check the sessionlist_subject_areas / describe_subject_area to see what data existsrun_graphql_query / query_subject_area to pull itexport_to_csv / sync_subject_area to land it locallylist_local_tables / query_local_data to work with what's syncedData lands in local CSV files and a DuckDB database the team can open in Excel or Power BI, or ask questions about in plain language through any MCP-capable assistant. Read-only by design. Set OPERA_MOCK=1 to try it offline with no credentials; smoke test: python -m unittest tests.test_opera_analytics_smoke. Server docs live in mcp-servers/opera-analytics/README.md.
Tools employees can actually use, from the systems they already have. The same pattern as the procurement work: take an awkward system of record, give people their own data back, charge for outcomes not visibility.
Data sources: Statistics Canada, Innovation Canada, Alberta Forest Products Association, Job Bank Canada
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