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Flux LinkedIn MCP

Create Stream

create_stream

Create a new research stream (external profile, company, topic, person interests, hiring signals, or ad watch). Running the stream on its schedule costs credits (see get_cost_estimate for the per-type cost). own_profile streams are not created here — they come from subscription checkout.

Input Schema

NameRequiredDescriptionDefault
nameYesUser-facing label for this stream
typeYesStream type
paramsNoType-specific config: topic uses {query, authorsIndustryId?, contentType?, postedLimit?, sortBy?}; hiring_signals/ad_watch use {company?, keywords?, ...}
scheduleNoRun schedule. Defaults to 'weekly'. 'monthly' runs every 30 days — the cheapest recurring cadence, and the usual choice for client profiles reported on monthly.
source_urlNoLinkedIn URL for external_profile / company / person_interests streams
history_daysNoHow far back the first run should reach, in days. Bounds the walk by TIME where initial_max_pages bounds it by COST — the run stops at whichever limit it hits first, so pair a window with enough pages to reach it. Honoured for external_profile, company and person_interests; the search types ignore it. Applies to this pull alone and is never saved on the stream, so scheduled runs keep topping up from where the last one stopped rather than re-fetching the window.
initial_max_pagesNoOpt-in deep first-run for external_profile, company and person_interests streams (1-5, default 1). A budget, not a price — you are billed for pages actually walked. A page is ~50 posts for profile/company feeds and ~100 engagement events for person_interests. Other stream types ignore this. Later scheduled runs pull one page in the steady state; a person_interests stream may walk further to close a gap after a missed tick, and is billed only for what it walks.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose the important trait that scheduled runs consume credits and that per-type cost lives in get_cost_estimate, plus the own_profile carve-out. It says nothing about permissions/scopes, what is returned on success (e.g. a stream id the agent would need for pause_stream or get_stream_feed), or what happens on duplicate names.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the action and the resource scope, then the cost caveat and the exclusion. No filler; every clause carries information an agent needs before invoking.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter creation tool with a nested `params` object and no output schema, the combination of a solid description and fully documented schema covers what an agent needs to call it correctly. The remaining gap is the return value — an agent is not told that it gets back a stream handle to use with list_streams, pause_stream, or get_stream_feed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the property descriptions are unusually rich — history_days and initial_max_pages are fully explained in the schema, not the description. The description only names the `type` values and the cost pointer, adding no syntax or format detail beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Create a new research stream') and enumerates the six stream types the tool supports, which maps directly to the `type` enum. It also distinguishes the resource from sibling creates (create_campaign, create_collection, create_segment) by naming exactly what a stream is.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit exclusion ('own_profile streams are not created here — they come from subscription checkout') and points to get_cost_estimate before committing, which is genuine pre-call guidance. It does not, however, contrast creating a stream with immediately running one (run_stream_now) or explain when a stream is preferable to a one-off search tool like search_posts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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