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IntegrationsMCP server

MCP server

Bidderops exposes a Model Context Protocol (MCP) server so AI assistants — such as Claude or Cursor — can securely read and act on your bid pipeline on your behalf. Instead of copy-pasting between tools, you can ask your assistant questions like “what deadlines are coming up this week?” and have it answer from live Bidderops data.

How a connection works

The MCP endpoint is an authenticated connection bound to your account. At a high level:

  1. Your assistant connects to the Bidderops /mcp endpoint.
  2. Because it is unauthenticated, the server points the assistant at its authorization server (standard OAuth 2.1 discovery).
  3. The assistant registers itself and opens an authorization page where you log in.
  4. After you approve, the assistant receives a short-lived access token tied to your session.
  5. Every tool call the assistant makes runs as you, under the same data isolation that applies in the app — so it can only ever see your organization’s data, and only what your role permits.

Connecting an assistant

Settings → Integrations is the home for the MCP connection: it shows your organization’s copyable MCP URL, the list of tools your plan makes available, and every assistant currently connected under your account. Paste the URL into your assistant’s MCP or connector settings and complete the sign-in it opens.

You can review and revoke connected assistants at any time from the same page. Revoking a connection invalidates its tokens immediately; the assistant would have to go through the authorization flow again to reconnect.

Available tools

Read

ToolWhat it does
list_opportunitiesList opportunities, optionally filtered by status or text.
get_opportunityFetch one opportunity with its notes, documents, milestones, team members, and outcome.
upcoming_deadlinesList active opportunities with a submission deadline within the next N days (default 14).
pipeline_summaryHeadline metrics: count by status, open count, open pipeline value, and win rate.
summarize_lossesGroup lost bids by loss reason and collect lessons-learned notes.

Write

ToolWhat it does
add_noteAdd a timestamped note to an opportunity.
create_opportunityCreate a new opportunity in your pipeline.
update_opportunityUpdate fields on an existing opportunity.
add_milestone / set_milestone_completeAdd a milestone, or mark one complete.
record_outcomeRecord a won/lost result and move the bid to that status.
add_team_memberAssign an organization member to the bid team.
add_document_linkAttach a document to an opportunity as a link.

AI

These run your organization’s own AI bid tools and use the model you have configured for each feature in Settings → AI. They are available when your plan includes AI bid tools; capability_match also requires the Experience & expertise feature, and the intelligence tools require the Bid intelligence agent feature.

ToolWhat it does
go_no_go_adviceGenerate a go/no-go recommendation with reasoning and factors.
analyze_rfpExtract scope, evaluation criteria, milestones, and key dates from RFP text.
capability_matchJudge how credibly you can deliver an opportunity from your experience and personnel.
pipeline_reportProduce a management briefing across the whole active pipeline.
generate_bid_intelligenceRun the web-grounded intelligence agent for a deep dossier.
get_bid_intelligenceRead the latest stored intelligence dossier for an opportunity.

Search and Experience library

ToolWhat it does
search_experienceFind company project references by sector, country, or keyword.
search_personnelFind experts by sector, country, or keyword, for staffing.
create_business_referenceAdd a company project reference, mapping a reference sheet or project document into structured fields.
create_personnelAdd an expert profile (CV), including the person’s assignment history.
search_sourced_opportunitiesBrowse the discovery inbox of externally-sourced tenders.
import_sourced_opportunityImport a sourced tender into your pipeline.

The four experience tools require the Experience & expertise feature; the discovery tools require Opportunity discovery. When you ask your assistant to add a CV or reference from a file, it maps the document into each tool’s typed fields — so the data lands in the right columns without manual entry.

Reads are available to any role; writes (and AI tools that persist a report) require an editor role, and that boundary is enforced by the database — not just the tool — so a viewer’s assistant cannot write even if asked to. Tools are only offered when your plan includes the matching feature.

Resources

Assistants that support MCP resources can browse and @-mention your pipeline directly:

  • bidderist://opportunity/{id} — a single opportunity with its notes, documents, milestones, team, and outcome (the same data as get_opportunity).
  • bidderist://pipeline/summary — your headline pipeline metrics.

Prompts

The server ships a few ready-made prompts you can pick in your assistant:

  • Weekly deadline digest — summarize the bids due soon and what needs attention.
  • Draft go/no-go — a go/no-go memo for one opportunity.
  • Loss retrospective — patterns and lessons from lost bids.
  • Bid kickoff brief — a one-page kickoff brief for a bid team.

Self-hosting the connector

A standalone MCP connector is also available to run yourself, either as a local subprocess (stdio) or as a small hosted service with the same OAuth flow. It covers the data tools (reads, writes, searches, and imports); the AI tools, resources, and prompts are served only by the built-in /mcp endpoint. Most teams should simply connect to the built-in endpoint — self-hosting is for environments with policies that require the connector process to run inside your own network.

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