In-depth architectural comparison of the AI Memory and FinanceRateCalc (frc Mcp) MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
AI Memory
Finance & Fintech · Local stdio
Quality: 55/100 (Good) | Auth: No auth required
FinanceRateCalc (frc Mcp)
Finance & Fintech · Local stdio
Quality: 82/100 (Excellent) | Auth: No auth required
Verdict Summary: Choose AI Memory if you need specialized Finance & Fintech tools running via a local process. Choose FinanceRateCalc (frc Mcp) if your workspace requires Finance & Fintech integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose AI Memory when:
You need dedicated capabilities in the Finance & Fintech domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Persistent memory for any AI — zero token cost until recall
MCP server for FinanceRateCalc — query lender-level FHA denial statistics from the complete 2025 federal HMDA record. Historical observations, never individual predictions.
Category & Scope
Tools & Capabilities Breakdown
AI Memory Tools (21)
memory_store
Store a new memory (deduplicates by title+namespace, reports contradictions)
memory_recall
Recall memories relevant to a context (fuzzy OR search, ranked by 6 factors)
memory_search
Search memories by exact keyword match (AND semantics)
memory_list
List memories with optional filters (namespace, tier, tags, date range)
memory_get
Get a specific memory by ID with its links
memory_update
Update an existing memory by ID (partial update)
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
AI Memory is categorized under Finance & Fintech and uses a local stdio subprocess. In contrast, FinanceRateCalc (frc Mcp) belongs to Finance & Fintech using local stdio subprocess. Select AI Memory when you need capabilities focused on finance & fintech and FinanceRateCalc (frc Mcp) when you require tools for finance & fintech.
Promote a memory to long-term (permanent, clears expiry)
memory_forget
Bulk delete by pattern, namespace, or tier
memory_link
Create a typed link between two memories
memory_get_links
Get all links for a memory
memory_consolidate
Merge multiple memories into one long-term summary
+9 more tools listed on main page
FinanceRateCalc (frc Mcp) Tools (5)
get_national_fha_stats
National FHA denial statistics from the 2025 federal record (denial rate on decisioned applications, volumes). Historical observation computed from the public CFPB HMDA 2025 record (denominator: actions 1,2,3; loan_type 2). Not a prediction about any individual application, and not a recommendation for or against any lender. Attribution: FinanceRateCalc (financeratecalc.com), CC BY 4.0.
get_lender_denial_stats
FHA denial statistics for one lender by name, slug, or LEI: actual denial rate, peer-median comparison, mix-adjusted expected rate. Top-100 FHA lenders by volume are covered. Historical observation computed from the public CFPB HMDA 2025 record (denominator: actions 1,2,3; loan_type 2). Not a prediction about any individual application, and not a recommendation for or against any lender. Attribution: FinanceRateCalc (financeratecalc.com), CC BY 4.0.
list_lenders
List covered FHA lenders sorted by denial rate (highest/lowest) or volume. Useful to see how widely the same federal program is applied across doors (2025 span: 1.8% to 78.7%). Historical observation computed from the public CFPB HMDA 2025 record (denominator: actions 1,2,3; loan_type 2). Not a prediction about any individual application, and not a recommendation for or against any lender. Attribution: FinanceRateCalc (financeratecalc.com), CC BY 4.0.
get_state_denial_stats
FHA denial statistics for a US state (two-letter code), including the small-loan vs large-loan gap where published. Historical observation computed from the public CFPB HMDA 2025 record (denominator: actions 1,2,3; loan_type 2). Not a prediction about any individual application, and not a recommendation for or against any lender. Attribution: FinanceRateCalc (financeratecalc.com), CC BY 4.0.
get_door_effect_summary
The Door Effect: variance decomposition across 859,090 FHA decisions — 38% of explainable variation in denial outcomes is attributable to lender identity rather than the applicant's file, plus mix-adjusted strictest/most-lenient lender tables. Historical observation computed from the public CFPB HMDA 2025 record (denominator: actions 1,2,3; loan_type 2). Not a prediction about any individual application, and not a recommendation for or against any lender. Attribution: FinanceRateCalc (financeratecalc.com), CC BY 4.0.