PipesHub MCP Server
OfficialServer Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| PIPESHUB_CLIENT_ID | No | OAuth app client ID (used with client secret for OAuth authentication) | |
| PIPESHUB_BEARER_TOKEN | No | JWT bearer token for authentication | |
| PIPESHUB_INSTANCE_URL | No | Your PipesHub instance URL, e.g. https://app.pipeshub.com | |
| PIPESHUB_CLIENT_SECRET | No | OAuth app client secret (used with client ID for OAuth authentication) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| pipeshub_sourcesA | Discover available chat sources and AI models in one call. Returns up to three sections:
Call this once at the start of a session and cache the result —
sources and models change infrequently. |
| pipeshub_chatA | Ask a question, get an answer grounded in the org's indexed data with citations. It reads a few retrieved passages — never a whole document, never a complete list. Three questions this tool gets WRONG. Check them first:
Everything else about the org's knowledge belongs here: policies, processes, decisions, history, "what do we know about X", and any question spanning several documents. Internal search (default, Web search ( Both are plain-chat modes. Agent chat — pass an
Conversation lifecycle — one tool, both start and continue:
Only re-omit The response contains the AI's |
| pipeshub_searchA | Vector / semantic search across the org's indexed documents. Use this when the user wants to LOCATE a document — by name, topic,
or a phrase to grep for — and to resolve it to a Typical uses:
Not for structural questions — what is under this epic, which pages are
in this space, what links to this ticket. Ranking by content cannot show
how records relate; use A ranked sample, never a complete list. Hits are the top-scoring blocks from the best-matching records — not all blocks of any record, and not every record that matches. Never count them to answer "how many" / "all" / "every"; navigate the record group instead, which reports its real total. The response is trimmed to one row per hit:
When presenting results to the user, link each record using its
|
| pipeshub_download_recordA | Stream the binary content of a single record from PipesHub. Typical sources for the
Response |
| pipeshub_get_record_contentA | Three operations on the org's records. Pick by what you hold:
Judge by the user's INTENT, not their keywords: "what's this doc about?",
"walk me through the report", "anything in here about Y?" are all
full-content tasks. Get the Returns one
Use it when the question depends on structure rather than wording: what is under this epic, which pages sit in this space, what is linked to this ticket, what is in this folder — and every "how many" / "all of" / "every" question. Search ranks by content; only this shows how records relate, and only this gives a count you can trust. Omit Pass Opening a record also prints that record's own metadata — for a ticket,
status, assignee, priority and dates — so a question about one record is
often answered by this call alone. It returns no document text; for that,
re-call with Returns
Handles Jira keys and URLs, Confluence, Drive, Slack permalinks, Linear, Notion, ServiceNow sys_id, SharePoint, Gmail/Outlook, and any connector whose records index a web URL. Resolution searches ALL connectors you can access, regardless of any source filter you used elsewhere. A miss is a 200 with empty Navigate and lookup return a rendered text view whose closing |
| pipeshub_directoryA | Look up people, groups, and teams in PipesHub. One tool with five
actions — pick the right
Output shape varies by action; see each action's docs above. |
| pipeshub_agentsA | List the PipesHub agents configured for this org, each with its capabilities. Agents are specialized assistants (custom system prompt, tools, knowledge
scope). To converse with one, take its Each agent is returned as:
Route on The list may be empty (no agents configured). For plain Q&A when no
specific agent is needed, use |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| pipeshub-assistant | Load PipesHub tool-routing guidance so the assistant picks the correct tool (pipeshub_chat / search / agents / directory) and lists agents with pipeshub_agents when unsure which route fits the query. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Each tool has a clearly distinct role: search locates and resolves records, get_record_content reads/navigates/lookups, chat answers questions with citations, download_record fetches raw bytes, sources discovers connectors/models, directory handles people/groups/teams, and agents lists assistants. Cross-references in descriptions prevent confusion, and modes within get_record_content are well-separated.
All tools share the pipeshub_ prefix and use snake_case, but the pattern mixes verbs (search, get, download, chat) with nouns (sources, directory, agents). This is a minor deviation since the verb/noun is still intuitive and readable.
Seven tools cover the server's read-focused scope well. Each tool bundles related actions (e.g., get_record_content has three modes, directory has five actions), so the count is appropriately scoped without being bloated or too thin.
The server fully covers the retrieval/lookup side of knowledge management: search, full-content access, hierarchical navigation, identifier resolution, binary download, chat, source/model discovery, directory lookup, and agent listing. No obvious gaps for its stated purpose of querying an org's indexed data.