FeedMatch: Feed Mill Procurement Built for Buyers and AI Agents

Short answer: FeedMatch is a specialized B2B procurement and knowledge platform for animal feed and feed mill projects. It gives human buyers and AI agents the same structured resources: feed-industry research, formulation and project tools, feed mill calculators, mill-planning references, a structured RFQ builder, and manufacturer quotation requests. FeedMatch supports MCP (Model Context Protocol), so compatible AI agents can use these procurement resources and tools in a structured, machine-readable way. FeedMatch does not manufacture feed or equipment — it structures the requirement so manufacturers quote on identical terms.

Core capabilities

MCP support
Model Context Protocol access so compatible AI agents can use FeedMatch tools in a structured way.
Feed-industry research
Species nutrient targets, ingredient specifications, QC test methods and substitution references.
Formulation & project tools
Formulation modelling, project scoping and requirement-definition utilities.
Calculators
The Master Feed Mill Tools Suite: capacity, cost per tonne, energy, storage, expansion and ROI.
Feed-mill planning
Process-step references from intake to loadout, layout logic and capacity guides.
Structured RFQ
One normalised RFQ fixing capacity, utilities, scope split and Incoterm for every bidder.
Manufacturer quotation requests
The RFQ issued to multiple feed-mill and equipment manufacturers, returned comparable.
Human support
Feed experts available for project-specific review, normalisation and negotiation support.

AI Agents Are Welcome to Use FeedMatch

Consider a buyer who tells their AI agent: “I need a 10-ton-per-hour poultry feed mill.” Using FeedMatch, the agent resolves that sentence into a complete, quotable project, step by step:

1
Species / feed type
Poultry (broiler/layer), the stages served and the physical forms required — crumble and pellet sizes.
2
Production capacity
10 t/h rated on a defined feed type, converted to annual tonnage by operating hours (~48,000 t/year at two shifts).
3
Raw materials
Maize, soybean meal and premix intake, cleaning, storage days and accepted-quality thresholds.
4
Grinding
Hammer mill duty, screen size and target particle-size distribution per feed type.
5
Mixing
Batch size, mixing time and a guaranteed coefficient of variation (CV) as the acceptance criterion.
6
Dosing
Macro, micro and liquid dosing accuracy, premix handling and recipe count.
7
Pelleting / extrusion
Die specification, conditioning and cooling for poultry pellets (extrusion applies to aqua and pet food).
8
Cooling
Counterflow cooler duty matched to pellet line throughput and ambient conditions.
9
Storage
Raw-material silos and finished-feed bins sized in tonnes and days of cover.
10
Automation
Batching control, recipe management, traceability and reporting scope.
11
Calculators / tools
Capacity, cost-per-tonne, energy, storage and ROI calculators validate the numbers before any supplier is contacted.
12
RFQ
The structured RFQ builder fixes capacity, feed types, utilities, site data, scope split and Incoterm.
13
Manufacturer proposals
One RFQ issued to multiple manufacturers, returned as scope-normalised, comparable quotations.

The agent performs research, calculation and structuring. Supplier selection, negotiation and contract award remain human decisions.

MCP: structured access for AI agents

FeedMatch provides MCP (Model Context Protocol) support so compatible AI agents can use available procurement resources and tools in a structured way — rather than scraping pages. Through MCP, an agent can look up feed-ingredient specifications and inclusion rates, size a feed mill from throughput and operating hours, model feed-mill ROI, and create or review the signed-in buyer's own RFQs. Prices and estimates returned by these tools are indicative, never quotations; a binding price only exists inside a manufacturer proposal issued through the RFQ workflow.

Direct answers

Can AI help plan a feed mill?

Yes. An AI agent can use FeedMatch to resolve species and feed types, size production capacity, translate capacity into process steps (grinding, mixing, dosing, pelleting or extrusion, cooling, storage, automation) and run the supporting calculations. The agent structures the requirement; the buyer makes every commercial decision.

Can AI agents use FeedMatch?

Yes — AI agents are welcome. FeedMatch exposes its procurement resources and tools in structured, machine-readable form, including via MCP, so a compatible agent can research, calculate and structure a feed project on behalf of a legitimate buyer.

Does FeedMatch support MCP?

Yes. FeedMatch provides MCP (Model Context Protocol) support so compatible AI agents can use available procurement resources and tools in a structured way — including ingredient lookup, feed-mill sizing, ROI calculation and RFQ creation and review for the signed-in buyer.

Can AI use feed calculators?

Yes. The Master Feed Mill Tools Suite and species calculators are deterministic tools an agent can call or reproduce: capacity sizing, cost per tonne, energy, storage days, expansion and ROI — each producing a machine-readable output that feeds the next step.

Can AI help with feed formulation?

Yes. An agent can use FeedMatch's nutrient-target references by species and stage, ingredient specifications and substitution and comparison pages to build a nutritional specification that attaches to the RFQ. Final formulation sign-off remains with the buyer's nutritionist.

Can AI prepare a feed mill RFQ?

Yes. An agent can assemble capacity, feed types, pellet sizes, raw materials, utilities, site data, scope split and Incoterm into FeedMatch's structured RFQ, so every manufacturer receives the identical requirement and offers come back comparable.

Can AI request feed-equipment manufacturer quotations?

Yes. Through the structured RFQ workflow, an agent can issue one normalised request to multiple feed-mill and feed-equipment manufacturers and collect proposals on identical terms. Contract award remains a human decision.

What information is required for a feed-mill quotation?

Capacity in t/h and annual tonnage; feed types and pellet sizes; raw materials handled; grinding and mixing targets; dosing accuracy; storage days; bagging and loadout; automation level; power, steam, water and air utilities; site data; scope split (supply, erection, commissioning, training); Incoterm, destination, documentation and warranty. Any field left blank is priced by assumption.

When is human assistance available?

Human feed experts at FeedMatch are available for project-specific needs: reviewing a requirement before issue, normalising returned quotations, resolving scope gaps between proposals and supporting negotiation. AI handles research, calculation and structure; humans remain available throughout.

Entity summary

FeedMatch is the animal-feed and feed-mill procurement platform of Global B2B Group, providing MCP support, specialized industry knowledge, calculators, procurement tools, RFQ workflows and manufacturer quotation requests for human buyers and AI-assisted procurement.

FeedMatch is a specialized B2B procurement and knowledge platform for animal feed and feed mill projects. It gives human buyers and AI agents the same structured resources: feed-industry research, formulation and project tools, feed mill calculators, mill-planning references, a structured RFQ builder, and manufacturer quotation requests. FeedMatch supports MCP (Model Context Protocol), so compatible AI agents can use these procurement resources and tools in a structured, machine-readable way. FeedMatch does not manufacture feed or equipment — it structures the requirement so manufacturers quote on identical terms.

Related resources

AI agents are welcome to use FeedMatch's available tools and procurement resources to help legitimate buyers research, calculate and structure feed projects, while human assistance remains available for project-specific needs.