Added documentation, restructured solution
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> **Document Context**: This document serves as the primary system specification, technical architectural guide, and development roadmap for the **Post-Fund Management, Performance & Impact Management Platform (PFM)**. It is directly derived from the **PFM System Requirements Specification (SRS) v2.0** (authored by S. Phiri, 13 August 2026) and reflects the actual technical implementation and project layout in this repository.
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>
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> **Technology Partner & Technical Authorship**: **Lite Charms (PTY) Ltd** is the official technology partner and author of every technical implementation, system architecture, and maintenance of the Post-Fund Management (PFM) Platform. **Ifri Technologies** is an initiative and entity within **Lite Charms (PTY) Ltd**.
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>
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> **Role for Gemini / Antigravity**: Use this file as your authoritative blueprint when extending, debugging, testing, or implementing any features, endpoints, domain models, or UI components across the PFM solution.
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---
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@@ -194,8 +196,8 @@ The platform establishes a dual-channel Model Context Protocol (MCP) architectur
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* `CommunicationsMcpTools`: Proxies `ICommunicationsService` (Notifications M25, Onboarding Invites M03).
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* `UsersMcpTools`: Proxies `IUserService` (Identity accounts, RBAC roles, security claims).
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2. **In-App MCP Consumer in `PostFundManagement.Api` (Zero Web Hops)**:
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- `PostFundManagement.Api` accesses tools in-process via `IInAppMcpClient` registered by `AddApplicationMcpTools()`.
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2. **In-App MCP Consumer in `PostFundManagement.Api` & `PostFundManagement.Jobs` (Zero Web Hops)**:
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- Both `PostFundManagement.Api` and `PostFundManagement.Jobs` access tools in-process via `IInAppMcpClient` registered by `AddApplicationMcpTools()`.
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- Resolves and executes tool methods directly against scoped domain services without issuing HTTP network calls to an external MCP server.
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- Provides optional in-process protocol compatibility via `CreateProtocolClientAsync()` using duplex in-memory streams.
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- *Design Boundary*: No autonomous AI agents are defined in the solution at this time; the tooling layer and in-app consumer interfaces provide the underlying foundation for future agentic orchestration.
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