Skip to main content
Glama

Recall facts at a cell (auto-materializes on miss)

emem_recall
Idempotent

Reads signed, citeable facts for a location cell, returning all primary facts for requested bands and auto-materializing missing values from upstream sources.

Instructions

Read the signed facts at a canonical address (cell64); auto-materializes on a miss for any band with a registered materializer. A fact_cid names one signed attestation, so a recalled fact is citeable and re-verifiable rather than a paraphrase: resolving it anywhere returns those exact bytes. It is NOT a fingerprint of the observation. The digest covers the responder's key and the moment it signed, so two responders that measure the same thing mint different fact_cids and a cid resolves only at the responder that signed it; use emem_entity for identity that crosses responders. Pass deterministic:true (or a provenance class list) to keep only facts recomputable from the cited raw source, with no model or human in the loop. In the memory algebra this is ensure(cell, bands), not get: state what must exist and the responder reuses or materializes.

When to use: Call after emem_locate (or with a known cell64). Returns every Primary fact stored at that (cell, band, tslot). IMPORTANT: if the cell has no fact yet for a requested band AND that band has has_materializer=true (per emem_coverage_matrix / emem_materializers), the responder fetches the upstream value, signs it under its identity, persists it, and returns it in the same response (slower on the first call while the upstream is fetched; fast once cached). So for any wired band you can recall ANY cell on Earth without seeding, just pass bands: [<band>]. The response carries materialize_notes listing what was just fetched. Empty result with no notes means the band has no materializer at this responder.

Example arguments: {"cell":"damO.zb000.xUti.zde78","bands":["weather.temperature_2m","copdem30m.elevation_mean"]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoExplicit latitude, an alternative to `cell`; paired with `lng`.
lngNoExplicit longitude, paired with `lat`.
bandNooptional single band key, convenience alias for bands:[band]. Use when you want exactly one band (e.g. 'geotessera.2020', 'modis.ndvi_mean') and would otherwise have to wrap it in an array. Both `band` and `bands` are accepted; if both are given they are merged.
cellYescell64 string, e.g. 'damO.zb000.xUti.zde78'
bandsNooptional band keys to filter, e.g. ['indices.ndvi','geotessera']
placeNoFree-text place name, an alternative to `cell`.
scopeNoOptional multi-tenant scope {user_id, agent_id, run_id, org_id}. When at least one field is set, the recall is FILTERED to facts written under the same four-tuple (a recall scoped to {user_id:'u1'} sees only u1's facts, never another tenant's and never globally-written facts) AND the signed receipt binds the scope. Omit (or send {}) for the global, pre-v0.0.8 recall.
tslotNooptional time slot (band-tempo-relative integer offset from emem epoch)
cell64NoAlias for `cell`.
includeNoOpt-in response expansion. include:['provenance'] attaches each fact's tamper-provenance class, which is what `deterministic` and the `provenance` filter select ON: without it you can filter by class and never be told which class a returned fact is. include:['freshness'] attaches an advisory per-fact freshness block: a Q(Δt) staleness score from the band's physics decay kernel (the same one /v1/temporal_route ranks bands with), so an agent learns how stale each reading is in the call that returns it. Advisory only; it does NOT enter the receipt. include:['edges'] attaches each fact's typed temporal edges and threads their CIDs into the receipt. Absent leaves the response byte-identical to the pre-v0.0.9 recall.
provenanceNoTamper-provenance filter: return only facts whose band's provenance class is in this list. `attested_execution` is a device reading trusted through its verified OS execution trace and platform attestation (not recomputable). Applied BEFORE the receipt is signed, so the receipt covers exactly the returned facts; `bands_already_attested_at_cell` stays unfiltered so you still see what else exists at the cell.
as_of_tslotNoBi-temporal valid-time bound. Returns the latest fact per (cell,band) whose tslot ≤ as_of_tslot, answers `what did this place look like AS OF date X`. Conflicts with an explicit `tslot` when as_of_tslot < tslot (rejected with code:`invalid_temporal_bound`).
deterministicNoSugar over `provenance`: true keeps only facts any third party can recompute from the cited raw source (direct_sensor + deterministic_index); false keeps the rest (attested_execution + model_output + human_curated + unclassified). Composable with `provenance` (intersection).
as_of_signed_atNoBi-temporal transaction-time bound. RFC 3339 string. Returns only facts whose `signed_at` ≤ as_of_signed_at, answers `what did emem KNOW as of system-date Y`. Malformed strings are rejected with code:`invalid_signed_at_format`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
factsYesSigned facts at the cell, ordered per fact_order.
receiptYesed25519 receipt over the returned fact_cids. Verify offline; select the rule from its preimage_version.
fact_orderYesThe ordering contract for facts, e.g. tslot_ascending. Stated rather than implied so nothing depends on position by accident.
current_by_bandNoPer band, the fact_cid with the highest tslot: the current reading. Unslotted facts are excluded, since tslot 0 means undated rather than oldest.
materialize_notesNo
bands_already_attested_at_cellNoWhat else is readable here without materialising, so an empty result can be told apart from a wrong band name.
Behavior5/5

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

The description discloses significant behavior beyond the annotations: auto-materialization fetches upstream, signs under the responder's identity, persists, and returns in the same response; it also notes slower first-call latency and the materialize_notes field. It explains fact_cid resolution semantics and the non-fingerprint property. This goes well beyond the readOnlyHint/idempotent/destructive annotations. No contradiction with annotations.

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?

The description is long but dense and well-structured: first paragraph explains core semantics, second provides when-to-use and auto-materialization behavior, third gives a concrete example. Every sentence adds distinct information; there is no filler or redundant repetition.

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

Completeness5/5

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

For a complex 14-parameter tool with annotations and an output schema, the description is remarkably complete. It covers materialization behavior, temporal/provenance options, cross-responder identity, and usage order relative to siblings. The return shape is not described, but an output schema exists, so that is acceptable.

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% at 14 parameters, and each parameter already has a thorough description. The tool description adds a bit of conceptual framing (e.g., `deterministic` as sugar over provenance, example arguments) but does not materially extend the parameter semantics beyond the schema. Baseline 3 is appropriate.

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?

The description opens with a specific verb+resource statement: "Read the signed facts at a canonical address (cell64); auto-materializes on a miss." It clearly distinguishes the tool from siblings by contrasting with emem_entity (identity across responders) and noting the relationship to emem_locate. The purpose is unambiguous and operationally precise.

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

Usage Guidelines5/5

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

Explicit when-to-use guidance is provided: "Call after `emem_locate` (or with a known cell64)." It also gives alternatives, stating "use emem_entity for identity that crosses responders" and explaining that this is "ensure(cell, bands), not get." This gives the agent clear decision criteria for tool selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Vortx-AI/emem'

If you have feedback or need assistance with the MCP directory API, please join our Discord server