Spectra Mcp Server

MetaVault MCP

Multi-protocol yield intelligence for AI agents — covering Spectra Finance, Pendle, and Morpho via the Model Context Protocol.

55 tools · 3 protocols · 10+ chains · read-only · open emergence architecture · calibration intelligence · on-chain Curve quoting · Pendle logit AMM modeling · ERC-4626 health checks · yield curve term structure · historical eth_getLogs · full Pendle protocol parity (15 tools) · cross-protocol position map · cross-protocol Spectra↔Pendle comparison · veSPECTRA + vePENDLE governance · Pendle historical time-series · Morpho supply-side visibility with supplier cascade modeling · Morpho user positions & historical rates · Merkl campaign APR + expiry integration · entry path awareness · prescriptive observation boundaries · curator risk monitoring · withdrawal stress testing · rollover planning · multi-vault portfolio aggregation · pool expiry monitoring · zero web3 library dependencies

What This Does

Any AI agent (Claude, GPT, open-source) that supports MCP can query Spectra, Pendle, and Morpho in a unified interface to:

• Discover the best fixed-rate yield opportunities across 10 chains simultaneously
• Analyze specific PT/YT positions with full data (APY, TVL, liquidity, prices)
• Calculate leveraged looping strategies (Spectra PT + Morpho collateral) with auto-detected borrow rates
• Compare fixed vs. variable yields to make informed decisions
• Track wallet portfolios across all Spectra positions (PT, YT, LP) with Merkl reward integration for complete PnL
• Surface external Merkl campaign APR alongside pool and market data for both Spectra and Pendle
• Monitor pool trading volume, individual transaction activity, and cross-pool address scanning
• Quote PT trades with on-chain Curve get_dy() for exact output, falling back to math estimates
• Simulate portfolio state after a hypothetical trade (BEFORE / TRADE / AFTER with deltas)
• Scan all chains for capital-aware opportunities with price impact, effective APY, and Morpho looping analysis
• Detect YT arbitrage opportunities where IBT APR diverges from YT implied rate
• Compute real veSPECTRA boost multipliers per-pool using live on-chain data from Base, and vePENDLE voting power from Ethereum mainnet (with sPENDLE transition awareness)
• Map your full cross-protocol position in one call — Spectra + Pendle + Morpho + governance (veSPECTRA + vePENDLE), with contradiction detection (unused boost, lending vs fixed rate spreads, concentration, looper detection, expiring positions across protocols)
• Assess entry path complexity — automatically flags exotic underlyings, sw-wrapper hops, and mainnet gas friction so agents know the real cost of reaching advertised yields
• Discover live MetaVaults across all chains — curator info, TVL, APY, positions, epoch history
• Model MetaVault "double loop" strategies for curators — vault compounding + Morpho leverage with curator economics, auto-populated from live API data or manual parameters
• Monitor MetaVault operational health — curator dashboard with vault allocation per position, depositor flows, fee revenue, bridge activity, and actionable alerts
• Query Morpho lending markets for PT collateral opportunities, identify who supplies the lending liquidity, and discover vault allocations across markets
• Query protocol stats, tokenomics, and governance data
• Compare Spectra vs Pendle yield opportunities side-by-side with maturity-aware matching on overlapping chains
• Scan both Spectra and Pendle for the best curator opportunities with capital-aware sizing and cross-protocol match tagging
• Browse Pendle markets across all Pendle-supported chains (including Pendle-only chains like Mantle, Berachain, HyperEVM, Corn)
• Analyze Pendle markets in full depth — market details, portfolio tracking, trade quoting, trade simulation, looping strategies, YT arbitrage, expiry monitoring, yield curves, capacity analysis, and protocol-wide stats (full parity with Spectra tools)
• Assess pool depth with multi-size capacity curves — quote PT trades at geometric capital tiers ($1K→$1M) to find the sweet spot and exhaustion point on both Spectra and Pendle
• Verify IBT health before deploying — on-chain ERC-4626 conversion rate, APR sustainability (organic vs incentive), pool balance, protocol recognition, liquidity
• Visualize yield curves (term structure) for any underlying across all chains — all maturities sorted chronologically with curve shape analysis
• Recover historical on-chain pool activity via eth_getLogs when API data has aged out — with dynamic RPC URL support for any chain
• Monitor curator Morpho position health — liquidation distance, borrow rate drift, health factors across all chains
• Stress-test MetaVault withdrawal scenarios — liquidity waterfall analysis (idle → maturing → LP removal → PT sale) with market stress simulation
• Plan position rollovers for expiring MetaVault positions — cross-protocol candidate ranking with entry impact, yield gap, and overlap windows
• Aggregate multi-vault curator portfolios — total AUM, blended APY, fee revenue projection, concentration analysis by underlying/chain
• Monitor pool expiry across all chains with readiness assessment — successor pool detection, gauge status from governance API, and operator checklist (deploy pool / submit gauge / ready for migration)
• Learn protocol mechanics on-demand via mv_get_protocol_context (PT/YT identity, Router batching, deposit paths, glossary, fees & costs, workflow routing, externalPositions registry)
• Surface protocol YT fees (Spectra 3%, Pendle 5%) and Merkl campaign eligibility (POOL vs HOLD) directly in tool output so agents apply them without external lookups

The agent doesn't need to understand PT/YT mechanics -- it just calls spectra_scan_opportunities or pendle_scan_opportunities with its capital size and gets ranked, actionable data. For cross-protocol comparison, mv_scan_curator_opportunities ranks both protocols together. If it needs to understand why something works that way, it calls mv_get_protocol_context.

Open Emergence Architecture

The server is designed so that AI agents can discover novel strategies without being taught specific strategies. Instead of hard-coding strategy identification logic, the system teaches protocol mechanics at three layers — and lets the agent compose building blocks into its own analysis.

The Three Layers

Layer 1: Protocol Context (mv_get_protocol_context tool + resources)
  → Teaches the "physics" of the protocol: PT/YT identity, Router batching, minting
  → Available as a callable tool (on-demand) and as MCP resources
  → Static knowledge — what CAN happen, not what IS happening

Layer 2: Tool Descriptions (every tool's description string)
  → Teaches domain-specific mechanics relevant to that tool's data
  → Cross-reference nudges: "use spectra_get_portfolio to check actual holdings"
  → Uses "could be" language, not "is" — preserves ambiguity where it exists
  → Calls out hidden mechanics that could mislead (e.g., AMM_ADD_LIQUIDITY can mint YT)

Layer 3: Structured Output Hints (computed at runtime in tool output)
  → Position Shape analysis in portfolio: balance ratios (e.g., "YT/PT 4:1")
  → Portfolio Signals: concentration, maturity alerts, strategy shape across positions
  → Volume Signals: volume/liquidity ratio, buy/sell skew, trend detection
  → Morpho Market Hints: capacity warnings, utilization alerts, spread analysis, reward incentives
  → Morpho Supply-Side Analysis: supplier identification (vault/EOA/looper), concentration metrics,
    supply gap warnings — surfaces where lending liquidity comes from and whether it's sufficient
  → Competing Interpretation Branches (A/B/C) in activity analysis per-address:
    multiple explanations for the same observable pattern, presented with equal weight.
    The agent must bring external evidence to collapse branches — the tension IS the info.
  → Statistical confidence boundaries: small-N cycle repetitions (≤5) flagged as
    insufficient for extrapolation, preventing false pattern-matching
  → Flow Accounting with competing hypotheses: YT-only, PT-only, fully exited positions
    each get multiple explanations that predict different future behavior
  → Address isolation mode: cycle detection, flow accounting, contract/EOA detection,
    pool impact warnings, gas estimates, pool context
  → Capital-aware warnings: short maturity, low liquidity, negative effective APY
  → Yield Dimensions in scan output: fixed, variable, LP, looping side-by-side
  → Strategy Tension: competing PT looping vs YT accumulation on same pool
  → On-chain quote source indicators: "(on-chain Curve get_dy)" vs "(estimated)"
  → Yield composition: IBT APR breakdown (organic base vs external incentives) in scans and quotes
  → Incentive sustainability: flags when >50% of IBT APR or LP APY comes from incentives,
    shows "organic only" APY so agents can assess yield durability without incentive assumptions
  → Pool reserves: IBT/PT amounts with ratio for AMM imbalance analysis
  → Merkl campaign APR: external incentive programs (e.g., KAT rewards) shown per-pool/market
    with double-counting avoidance (skips campaigns whose reward tokens are already displayed)
  → Merkl campaign eligibility: action type (POOL/HOLD) always shown, with explicit
    "[LP only — not for YT/PT holders]" flag on POOL campaigns to prevent misattribution
  → Protocol YT fees: Spectra 3% and Pendle 5% shown in every pool/market detail output
    so agents apply them to yield calculations without needing external lookups
  → Points multipliers: external programs (Drops, InfiniFi, Firelight) with amounts
  → "Could be" / "at current rates" language: preserves ambiguity in ranked output
  → Makes key signals SALIENT without prescribing interpretation

Layer 4: Observation Coverage (quantifies blind spots in tool output)
  → Value coverage: what % of an address's position is explained by observable activity.
    Low coverage means most behavior is invisible (direct mints, transfers, cross-chain).
  → Temporal coverage: active days vs dark periods with no observable events.
    Longest gap duration surfaced so the agent can reason about invisible activity.
  → Data source coverage: which of 5 available sources were consulted vs not.
    Explicitly lists what is invisible to the current analysis.
  → Activity diversity: single-type activity flagged as highest-ambiguity pattern.
  → Boundary marker: "Position sizing should assume this analysis is incomplete,
    not comprehensive." — a structural admission of domain-of-validity limits.
  → Coverage metrics bound ALL interpretations above them. High-confidence strategy
    assessment + low observation coverage = false confidence. The coverage section
    forces the agent to size its conviction to what it actually observed.

Design Principles

• Teach mechanics, not conclusions. The server explains that AMMADDLIQUIDITY could be a mint+LP batch operation — it doesn't conclude "this user is accumulating YT."
• Present competing interpretations, not single narratives. Activity analysis outputs multiple interpretation branches (A/B/C) that predict different future behavior. The agent must bring external evidence to collapse them. This friction surface prevents premature pattern-matching — the most common failure mode in wallet strategy analysis.
• Flag statistical insufficiency. Small repetition counts (≤5 cycle detections) are explicitly flagged as insufficient for extrapolation. The agent cannot treat N=3 as a confirmed pattern.
• Every tool cross-references at least one other tool. This creates analytical workflows without dictating them. The agent learns to check spectra_get_portfolio after seeing activity patterns, not because it was told to.
• Hidden mechanics are called out where they can mislead. The Spectra Router batches multiple operations atomically. A SELL_PT event might actually be YT acquisition via flash-mint. Tool descriptions teach this so agents don't draw wrong conclusions from pool data alone.
• Full addresses in output, never truncated. When addresses appear in activity data, they're shown in full so the agent can pass them directly to spectra_get_portfolio without needing a block explorer.
• Discovery tools warn about capital-awareness gaps. spectra_get_best_fixed_yields explicitly says "this ranks by raw APY — use spectra_scan_opportunities for capital-aware sizing."
• Quantify blind spots, not just interpretations. Tools now output observation coverage metrics: what percentage of behavior is visible, what data sources were consulted vs available, and how long dark periods lasted. These are not interpretations — they're structural measurements of the analysis's own incompleteness. An agent that sees 35% value coverage should size its confidence accordingly, regardless of how coherent the best-fitting interpretation looks.

Why This Matters

A cold-start agent with zero prior knowledge of the protocols can:

1. Call mv_scan_curator_opportunities — see cross-protocol (Spectra + Pendle) yield rankings with capital-aware metrics
2. Call spectra_get_pool_activity — see trading patterns with ⚠ hints about ambiguous events
3. Call spectra_get_portfolio and pendle_get_portfolio on flagged addresses — see Position Shape across both protocols
4. Read the cross-reference nudges — compose its own analytical workflow spanning all three protocols
5. Identify novel strategies the server was never explicitly programmed to detect

This was validated: a subagent spawned with zero priming correctly identified a mint-and-sell-PT loop strategy (YT accumulation via PT discount) in 3 tool calls, using only the mechanics taught in descriptions and the structured hints in output.

The competing-branch design was motivated by a real failure: an agent analyzing a multi-chain wallet collapsed all activity into "YT accumulator" despite different pools showing different patterns (spread capture, market making, LP cycling). The single-narrative failure mode — where the agent picks one interpretation and defends it — is the most dangerous because it looks like good analysis from inside.

The observation coverage layer addresses a deeper problem: even perfect interpretation of observed data is misleading when the data covers a minority of behavior. Competing branches solve the narrative problem (which story fits?). Coverage metrics solve the exposure problem (how much of the picture am I seeing?). An agent that picks the best interpretation branch but ignores 65% invisible activity is sizing conviction to coherence, not evidence.

Tools

| Tool | Description | |------|-------------| | spectra_get_best_fixed_yields | Scan ALL chains for top fixed-rate opportunities. The main discovery tool. Supports compact mode. | | spectra_list_pools | List all active pools on a specific chain, sorted by APY/TVL/maturity. Surfaces pool reserves, IBT APR composition, maturityValue, multipliers, and tags. Supports compact mode and include_expired flag. | | spectra_get_pt_details | Deep dive on a specific Principal Token -- full data including maturityValue, multipliers (points programs), tags, pool reserves, IBT APR composition, and baseIbt for wrapper tokens. | | spectra_compare_yield | Fixed (PT) vs. variable (IBT) yield comparison with spread mechanics and entry cost analysis. | | spectra_get_looping_strategy | Calculate leveraged yield via PT + Morpho looping with effective liquidation margins, borrow rate sensitivity (+1/2/3%), break-even period, and failure scenario modeling. Auto-fetches live Morpho rates when a matching market exists. | | `morpho_

…

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Finanzgoblin
• Source: Finanzgoblin/spectra-mcp-server
• License: MIT

Install and usage instructions live in the source repository linked above.